The facial recognition market is growing rapidly and this technology is being used in various sectors across the globe.
Gone are the days when we used to see face recognition technology in Sci-fi movies. Today, even a budget smartphone has a face recognition feature.
According to Statista, the global facial recognition market will grow at a compound annual growth rate of around 15.4% to reach 12.67 billion USD by 2028 from 5 billion USD in 2021.
The facial recognition system is used in schools, hospitals, banks, and many other places. Let’s see some amazing uses/trends of the facial recognition system.
Nowadays, facial recognition systems are used in various places. These include banks, hospitals, traffic signals, airports and more. The following are some of the most popular uses of facial recognition systems:
Facial Recognition Market Size Worldwide in Selected Years from 2019 to 2028
Finding Missing Children
Face recognition CCTV systems can be used to find missing children by allowing police to add a reference photo provided by the missing child’s parents and match it with past appearances of that face captured on video.
To find the time and location where the child has been declared missing, the police will use face recognition to search video sequences (video analytics).
In this way, the police can find out where the child was last seen. A real-time alert can trigger an alarm whenever there is a match.
In 2018, Delhi police traced 3,000 missing children using the facial recognition system.
Track Criminals
Using the same face recognition CCTV systems, police can track past criminals suspected of committing a crime.
Police can use the image of past criminals from their database to detect matches in live video.
Help the Blind
Listerine has developed a face recognition app that helps blind people. The app recognizes when the people around the blind person are smiling and vibrating.
This can help blind people better understand social situations and react in a better way.
Track College Attendance
Facial recognition can be used to track college attendance. Currently, to track attendance in college, students need to sign an attendance sheet.
But, the loophole here is that any student can sign for another student who is bunking the class.
Facial recognition ensures that attendance is recorded properly by tracking every student’s face. In China, tablets are used to scan students’ faces and match their photos against the database.
We have already seen electric cars but, did you imagine unlocking your cars with simple face recognition? China’s Byton has revealed a concept where users will be able to unlock their cars using face recognition.
In the future, the door handles or the engine will remain locked until the registered user sits in the car.
Diagnose Diseases
DiGeorge Syndrome Diagnosis – Uses of Facial Recognition System
Diseases that cause detectable changes in appearance can be diagnosed by the facial recognition system. This helps the healthcare industry experts to detect certain diseases in the early stage.
The National Human Genome Institute Research Institute is already using the facial recognition system to detect DiGeorge syndrome. It has helped diagnose the disease in 96% of cases.
Advertising is a make-or-break thing for any brand. If the advertisements resonate with the consumer then the conversion rates will eventually rise.
Facial recognition can help brands suggest better products to consumers after knowing their age and gender.
Airport Boarding
At present many airlines are using onboard facial recognition technology. More than 15 airports have face-matching systems in the US to help speed up the boarding process. Trials have taken place at Los Angeles airports among many others. In fact, this technology is making a lot of buzz in Europe too.
Recently, on the occasion of the 75th Independence day, the facial recognition system for passenger verification was launched in Delhi and Bengaluru airports.
A beta version of the DigiYatra was launched for android users where the app will automate passenger entry and verification at all touchpoints – airport entry, security check and boarding gate.
Conclusion
In the near future, the facial recognition system will become a necessity in marketing, hospitals, banks, and everywhere else. Biometrics technology has a lot of power and can revolutionize many things. It can make our lives easy and help speed up all the time-consuming things. As you can see from the above examples, the possibilities to use this technology are endless. Things that we used to see in the movies can now become a reality.
FAQs
How does a facial recognition system work?
A facial recognition system tracks your facial features and compares them with a database of photographs and videos.
How is facial recognition being used today?
The facial recognition system is used to track criminals, unlock cars, find missing persons and in targeted ads.
What are the problems with facial recognition?
Privacy concerns, lack of transparency and data breaches are some of the concerns related to facial recognition.
Artificial Intelligence or AI is the ability of machines to perform certain tasks that typically require human intelligence. It allows the machines to understand and achieve specific goals. Simplistically, machines learn, automatically, from existing data without being assisted by human beings.
When machines are able to absorb huge amounts of unstructured data such as text, images and audio, it is called deep learning. There are four types of Artificial Intelligence –
Reactive Machines
Limited Memory
Theory of Mind
Self- Awareness
Human beings, today, are surrounded by examples of Artificial Intelligence and that way it has permeated our day-to-day existence.
AI is advancing at a break-neck speed, similar to the exponential growth witnessed by database technology in the late twentieth century. The importance of data has been amplified by AI’s large appetite to store, retain and analyse data.
‘Metaverse’ was a term that was first heard in the 1992 science fiction novel ‘Snow Crash’. At that time, it was considered too futuristic and a concept of science fiction. Yet, less than 30 years later, it is on the verge of becoming a reality.
The metaverse is a single, universal and immersive virtual world. In simple words, it is an alternate universe facilitated by virtual reality and augmented reality.
There are existing uses of a metaverse in the gaming industry. This could very well leap into the everyday world. Be it conferences, meetings, weddings or parties, the metaverse can host it all. The possibilities of its uses are endless.
AI vs. Human Creativity – Can AI Take Over Creative Jobs?
Human beings are trying to achieve a system that emulates our intelligence. Achieving this requires a starting point. What is that starting point? A massive amount of data.
If we want a computer to tell us the difference between a tiger and a lion, we have to first feed it with thousands of images of tigers and lions. However, human intelligence is a multi-faceted tool.
A tool with the ability to make decisions, create, learn, evolve, draw inspiration from a lifetime of experiences, feel, empathize, think differently and, essentially, be a square peg in a round hole.
“Our intelligence is what makes us human, and AI is an extension of that quality.” ― Yann LeCun
Creativity
Albert Einstein says – “Creativity is seeing what everyone else saw, and thinking what no one else thought”.
The best example of this is probably, the advertising industry. This industry has, possibly, made the best use of AI. It has created award-winning campaigns. ‘The Next Rembrandt’ is a perfect example of how AI can be utilized optimally to understand the Dutch Master’s painting style, his use of colour, lights, his subject interest, etc. All this data can then be used to produce a modern painting emulating his style.
Yet, machines can never know, if Rembrandt himself would have evolved or if he might have shifted his interest towards another style of painting or subject.
Empathy
Empathy is the understanding of the problems and realities of the people and then designing the best product based on that understanding. AI can collect and collate data, but can never show the true nature of what drives human beings. Data can show an individual’s activity spanning days or months, but cannot answer the ‘why’ of those activities.
It is this particular human quality that separates us from AI. It is this quality that allows humans to design and create products with a deeper informed decision.
Mind Theory
Human psychology is a web of emotions that affect thought and behaviour. For AI to replace creativity, it would need the capability to comprehend human complexities and make decisions based on self-reflection. Currently, this is beyond the AI technological brilliance.
Conclusion
The superior intellect of human beings has led to the invention of Artificial Intelligence. Yet, it is a system that is based on rules and algorithms and built-in data. It is a system that relies on those very rules and algorithms to process the data that has been fed to it. Can it collate, relate and process data faster than human beings? Without a doubt. Can it scale imaginative heights and then further push its limits? No.
Human beings are not only gifted with intelligence but a natural curiosity to expand and grow. Continually push limits. Consistently evolve. AI is a tool that has been created to assist in our journey towards that excellence. Nothing more, nothing less. AI is a convenience that we created so we may continue to excel at our own imaginative brilliance.
FAQs
What jobs will AI take over?
Customer service executives, Bookkeeping and data entry, Proofreading, Manufacturing and pharmaceutical work, Retail Services, and Courier services.
What jobs will AI not take over?
Human resource managers, Writers, Lawyers, Psychiatrists, and Event planners are some of the jobs AI will not take over in of near future.
The mimicry of human intelligence is called Artificial Intelligence. Or the development of intelligent machines, thinking, and working like humans is called Artificial Intelligence. With the help of machine learning, we can develop Artificial Intelligence.
Machine Learning is an application of Artificial Intelligence that study the computer algorithm, learns automatically, and improves the experience. The computer, robotic machines, and machines have to learn how to respond in actions, it uses computer data structures and algorithms to create the Propensity Model.
The Propensity Model is a statistical model that is used to predict the behavior of your customer. The best example of artificial intelligence that we are using in our daily life is speech recognition like Alexa and Siri, problem-solving, learning, and planning.
How Artificial Intelligence is Helping in Business Today
Artificial Intelligence tools are supporting tools in our businesses today. It can work in the replacement of humans but it is facing many difficulties to complete common sense tasks in the real world. Artificial Intelligence is a form of software that can process and analyze data processes more quickly than human brains.
It can also return some actions and present them to human users. Artificial Intelligence can make decisions as opposed to traditional software. It can make the decision even in such a situation that has not been foreseen by the programmers before. It is very helpful in maintaining the relationship between the customers and the company.
Artificial Intelligence is changing the customer relations management system(CRM). High human intervention companies like Zohoand Salesforce have to remain up-to-date and accurate. AI helps these platforms to transform the customer relation management system into auto-correcting and self-updating that makes the best interaction with customers for you.
Artificial Intelligence In Business
Artificial Intelligence in Finance
Financial services are very important and too much use of AI in this industry. According to the McKinsey report, some companies have seen a profit margin of over ten percent higher than the industry average.
Artificial intelligence in finance can prove to be way much beneficial for the users. The decisions required in the financial sector might be needed to have a thorough check. With the help of AI, the work of checking the accounts can rarely take some time.
Also, it is scientifically proven that AI can make better data-driven decisions. AI can also help in financial service by completing some of the repetitive tasks in less time than human beings and with much proficiency.
The above graph shows the revenue collected from the artificial intelligence market worldwide in millions of US dollars for the years 2016-2022
Financial Services Using Artificial Intelligence
Financial services have seen a great peak in the use of artificial intelligence in their working pattern. Some of the most common uses are stated below.
Fraud Prevention
AI is used to increase revenue and cut the cost of the company. It is also very helpful in fraud prevention. In 2016, $16 Billion was stolen by fraudsters or identified as theft. The AI detects the client’s behavior, activities, locations, and buying habits that seem suspicious and unusual.
Trading
Artificial Intelligence and machine learning are very helpful in trading. They can gather data quicker than humans which helps to improve each day. It helps to eliminate the emotional aspects of trading.
Personalized Banking
Many banks and fintech companies are using AI to make better customer relationships and better service.AI helps the customer to understand the risk factors of various policies. It can create your financial plan by tracking your spending pattern, income, and goals.
Artificial Intelligence in Marketing
The marketing industry gets a boom with the development of AI. It helps to gather more and more data to create the best marketing plan and able to enhance marketing practices as well.
Marketing Attributes
It is very difficult to quantify the impact of various marketing channels like offline marketing TV, and Radio Billboards. To overcome this problem we need to execute two popular marketing techniques:- The attribution model and the marketing mix model.
An attribution model is a set of rules or analytical science determining the tactics of marketing contributing to sales or conversion. A marketing mix model is a marketing technique that is used to promote the brand product and services in the market.
Customer Profiling
An example of how customer profiling is carried out by AI
Customer profiling is a way to create the profiles of customers to understand decision concerns for your business. By creating profiles the customers are divided into smaller groups and a representative is given to each group with a photo, name, and description.
Logistics is an important part of each industry. With the combination of Artificial Intelligence logistics becomes more efficient by creating AIapplications like automated warehouses and automated vehicles.
Automated Warehouse
The above images show the use of robots in the fully automated warehouse
In an automated warehouse, thousands of robots are moving from point A to point B to fulfill the demand. The automated warehouse also reduces the cost of transportation, less warehouse space needed, and reduces overall costs.
Automated Vehicles
With the development of AI, it is very important to develop autonomous vehicles. The development of autonomous vehicles is very helpful for humans, they need rest and sleep while driving which leads to late delivery, now no longer transportation is limited.
Tesla is the best example of autonomous vehicles. Rolls-Royce cars and Intel are also in the queue of developing autonomous vehicles but they are very less known. Together they built an Intelligence Awareness System to allow the autonomous chips.
Artificial Intelligence in Retail Market
The retail industry is one of the most competitive industries. They need new inventions and technology to stand out from the crowd. AI in the retail market is applied in various processes of the retailer’s products and service cycle.
Chatbots And Robot Assistants
Google also has its own AI-based chatbot named “Meena”
The chatbot is an application of artificial intelligence which is used as a conversational agent. They communicate with visitors by using two primary methods:- web-based applications and standalone applications. For example, Pepper is a social humanoid robot designed by Softbank that is used in physical stores to engage customers and provide personal assistance to the customers.
Artificial Intelligence in Telecommunication
The Telecom industry is one of the biggest industries in the world. The value of this industry is very large so every difference matters. Three main artificial intelligence applications are used in the telecom industry:-
Churn Prediction Modelling
The prediction of detecting customers who are likely to cancel the contract or subscription is called churn prediction, It is very important as it gives a better understanding of future revenue. Churn prediction helps us to identify the areas of lacking customer service in your business.
Network Optimization
The improvement of the network is called network optimization. There are various ways to improve and monitor network performance:- global load balancing, minimizing latency, packet loss monitoring, and bandwidth management. By using artificial intelligence in network optimization we can increase speed, scalability, and effective result.
Predictive Maintenance
Predictive Maintenance refers to the monitoring of the condition of in-service equipment to reduce the risk of failures. It is also known as condition-based maintenance. By using artificial intelligence it can maintain the historical data, sensors data, and weather data to ensure the proper condition of a machine or when the machine needed servicing.
No one can say the future of artificial intelligence but you can predict the future of artificial intelligence. For example, artificial intelligence is ready to do common-sense tasks and it is easily handled by computers. We can say that robots are going to be a part of our day-to-day lifestyle in the future. Tesla is also innovating driverless cars and many companies are trying to innovate with AI technology. In the future artificial intelligence is going to lead our life.
Artificial Intelligence stands for the power of machines to behave like humans and possess a similar tendency to take decisions. With increasing technology, there is a significant growth noticed in AI projects. In today’s world, many services are dependent on AI.
The basic examples of AI include help desk solutions provided by chatbots, banking software uses AI to make their work easy, etc. The above article details the changes brought by AI into the business world and how it is developing regularly.
FAQs
How AI is changing the future of business?
Artificial intelligence allows business owners to provide a more personalized experience to their customers. AI can analyze vast data way more efficiently. As for the future, AI can prove to be more than just a help for businesses and many work will be AI-dependent.
What is Artificial Intelligence in Business?
Artificial intelligence (AI) refers to the ability of machines to understand the world around them, learn and make decisions, similar to the human brain. Thanks to AI, machines are getting smarter every day.
What are the benefits of artificial intelligence?
Artificial intelligence has many advantages in store for its opponent. Some of them can be minimal errors in work, improved customer satisfaction, fast-paced work, and automation of work.
How AI can solve business problems?
AI can solve business problems based on multiple factors. Some of the most common problems that can be solved by AI are security, scheduling and setting up appointments and working schedules for employees, improving customer and employee connections, etc.
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The focus of healthcare has been shifting toward the patient for quite some time now. The expansion of the health-tech industry is being driven by the availability of inexpensive healthcare paired with sustainable mobility. The medical technology business is growing due to changing terrain, improved healthcare delivery and funding methods, and a changing patient profile.
Even with all its flaws, India’s healthcare system has a lot moving for it on several fronts. Artificial intelligence can make accurate conclusions possible when it comes to patients’ data, thereby helping the patients achieve the healthcare quality they dream of. The government-led campaigns along with the companies like MFine are making the reach of healthcare broader and refining the healthcare practices to a huge extent.
MFine is an AI-powered, on-demand healthcare startup that gives customers access to online appointments and hospital-based linked healthcare. Telemedicine and teleconsulting programs via the MFine app are allowing medical knowledge to reach people much more easily and conveniently.
MFine merged with LifeCell International’s diagnostic arm on July 11, 2022, after being an independent company for over 5 long years. The new, merged entity will emerge as LifeWell.
Here’s learning “What is MFine?”, MFine owner name, Founders of MFine, MFine Funding, MFine Competitors in India, MFine merger, and everything else about the MFine company. Follow below to get an insight into the company:
MFine is an AI-powered on-demand healthcare startup that gives customers access to online appointments and hospital-based linked healthcare. Users can contact paediatricians, gynaecologists, obstetricians, and physicians from leading hospitals of their choice through chat or video to acquire prescriptions and/or routine treatment using the company’s service.
The doctors have exposure to a proprietary Assistive Intelligence platform that analyses symptoms and provides an accurate prediction for specialists to evaluate patients. This implies that now the doctor is aware of the patient’s condition even before they visit them, allowing for a quicker and more accurate diagnosis.
MFine aspires to make obtaining reliable healthcare simple, quick, and preventative. MFine was created by keeping the customer experience in mind, using a combination of cutting-edge technologies and collaborations with the finest medical centres.
MFine enables rapid and ongoing communication with the greatest doctors in the best hospitals. It makes use of cutting-edge technology to keep track of your health indicators and to keep all of your health data under your control and accessible. Digital wearables, smartphone apps, and at-home services provide much-needed ease and speed in bringing you the treatment you need when you need it. Furthermore, MFine also provides discounted health check packages in partnership with the hospitals.
According to research, India’s health market is predicted to develop at 39% at CAGR (Compound Annual Growth Rate) from FY2020 to FY2023, reaching 50 billion USD by 2033.
The health-tech market is presently valued at over $2 billion, and it is divided into six segments: telemedicine, e-pharmacy, fitness, wellness, healthcare IT, analytics, home healthcare, and personal health management. This represents less than 1% of India’s total healthcare business.
“The pandemic and adoption of technology in healthcare have brought a quantum shift in the sector. In recent years, we have seen some of the most significant deals, and the Indian health-tech sector has received close to $1.6 billion in funding since 2017,” said Rajeev Shah, MD, and CEO of RBSA Advisors.
According to the estimates, the Indian health-tech industry would reach $5 billion in 2023 and $50 billion in 10 years. With $700 million in revenue in 2020, e-pharmacies were the most profitable segment of the Indian health-tech market, followed by B2B health-tech ($60.2 million), B2B medical supplies ($28.8 million), other health-tech services ($100 million), e-diagnostics ($70 million), and teleconsultation ($45 million).
Machine learning, robotics, artificial intelligence, wearables, on-body gadgets, and blockchain, among other technologies, will have a significant impact on the future of healthcare. The use of cloud infrastructure in healthcare record management, as well as a greater focus on the digitalization of patient medical records, is expected to accelerate.
MFine – Name, Logo, and Tagline
MFine, as the name implies, shows what the firm does for its consumers, i.e., the patients. The mfine company makes it easy or patients to check up with physicians online and receive health tests at home, all with touch or the click of a button, thereby ensuring that they are fine.
MFine Logo
MFine’s slogan says, “MFine – one app for all your health needs.”
MFine – Founders
MFine was founded by Ajit Narayanan, Arjun Choudhary, Ashutosh Lawania, Prasad Kompalli in 2017.
Founders of MFine – Ajit Narayanan, Arjun Choudhary, Ashutosh Lawania, and Prasad Kompalli
Ajit Narayanan
Ajit Narayanan
Ajit is an electronics engineer with over 2 decades of experience in product development and organization building in e-commerce, consumer internet, mobile, healthcare, analytics, and integration platforms.
As a Co-founder, CTO, and Product Office of MFine, Ajit is in charge of the company’s product and technology strategy. Ajit was the CTO of Myntra, India’s largest e-commerce shop for fashion and leisure items, in a prior life. Ajit began his career in mobile technology at SAP, where he developed solutions for offline and online mobile application development, as well as domain programming languages for User Interfaces and API administration.
Arjun Choudhary
Arjun Choudhary
Arjun Choudhary, an IIT Roorkee alumni with over 10 years of expertise in sales, revenue, and growth, is in charge of the company’s Strategic Business Expansion. Before joining MFine, he worked at Myntra as a Senior Director of Growth and Sales, where he helped the company grow by 50 times. He’s also worked as a global capacity planning analyst for Amazon. Arjun is currently serving as the Chief Business Officer at MFine, along with being a Founding Member of the company.
Ashutosh Lawania
Ashutosh Lawania
Ashutosh Lawania is a software application developer and digital marketer with over 15 years of expertise. Ashutosh is known as one of the co-founders of the healthcare app MFine. He has also been the Co-founder and Head of Sales and Marketing at Myntra, an Indian e-commerce website where men and women can buy branded footwear, clothes, and accessories.
Before joining Myntra, Lawania co-founded Bytedge Solutions, a product engineering firm that specializes in assisting product development firms and startups with their product engineering and go-to-market processes. Lawania graduated from the Indian Institute of Technology in Kanpur with a Bachelor’s degree.
Prasad Kompalli
Prasad Kompalli
Prasad Kompalli, the former CBO of Myntra and Senior VP of SAP Labs, believes in harnessing technology for innovation, and his area of expertise is business strategy. He was a member of SAP’s top 200 worldwide executives, holding positions in Strategy and General Management. He completed his Postgraduate studies in Business Management at the European School of Management and Technologies (Berlin), IMD Switzerland, and INSEAD France, and he possesses 7 patents in data and mobile technology. Kompalli is known as the CEO and Co-founder of MFine.
MFine was last registered with a total count of employees ranging between 501-1000, on its Linkedin profile.
Ashutosh Lawania and Prasad Kompalli, both former top executives of Myntra, chose to start from scratch at the end of 2016. They’d helped Myntra grow into a great e-commerce consumer brand, but they noticed something similar was missing in healthcare. That was how MFine’s idea came to their mind.
MFine was founded in February 2017 as a healthcare platform. While they were not strangers to founding a business, MFine was a new experience for them. “It wasn’t easy persuading folks to join us and work with us when MFine was simply a notion on paper,” explains Kompalli.
Conversations with hospitals revealed that the customer experience needed to be improved.
“They needed an easy interface with limited typing, so we came up with a health keypad which collects data from reports without the user having to type. We ran a beta program and the results were promising,” Kompalli say
It was difficult for anyone without a medical or healthcare background to break into the healthcare ecosystem. Catching the early adopters, according to the creators, was challenging. People, on the other hand, quickly adapt to accessibility and ease.
The business accepts 100-120 cases every day from a variety of specialities. The business has collaborated with 20 hospitals in Bengaluru and has 70 doctors across ten specialities, offering voice, video, and chat support. The company’s founders are currently focusing on chronic illness management and the use of IoT to link medical equipment.
MFine – Vision and Mission Statement
MFine’s mission statement is to make quality healthcare available to consumers at scale.
MFine’s vision has always been to make excellent health more accessible, dependable, and hassle-free for everyone, driven by a love for providing care, spurred by an uncompromising emphasis on quality, and guided by ground-breaking artificial intelligence.
MFine – Business Model and Revenue Model
Instead of collecting individual physicians on its platform, MFine uses a unique methodology of working with prominent and trustworthy institutions. MFine can provide high-quality treatment from trustworthy doctors via a digital channel because of its hospital affiliations.
Gynaecology, dermatology, paediatrics, cardiology, and general medicine are among the app’s most popular specialities. Commissions from client consultations, lead-generation fees from hospitals, and corporate tie-ups are the main sources of revenue for the firm. It also has partnerships with local hospitals to provide accessible and dependable medical treatment.
MFine earns money by acting as a digital extension of its healthcare partners. That is, it deducts a portion of consumer expenditure. The firm claims to deal with over 500 doctors from 100 “elite” institutions, with a strong emphasis on technology.
MFine – Funding, and Investors
MFine, to date, has obtained $94+ mn over the 7 funding rounds that it has received funding in. The last funding round of MFine was the Series C round that came in on August 31, 2021, which was led by BEENEXT and Moore that poured in $46.39 mn. The company has been valued between $450-500 mn after the completion of the last funding round.
MFine has raised 7 rounds of funding. Check them out below:
Date
Round
Amount
Lead Investors
Aug 31, 2021
Series C
$46.39M
BEENEXT, Moore Strategic Ventures
Jan 18, 2021
Venture Round
$16M
Heritas Capital
Aug 31, 2020
Series B
$5.09M
Caretech Pte Inc
Jul 2, 2019
Debt Financing
$4.5M
Alteria Capital
Apr 22, 2019
Series B
$17.2M
SBI Ven Capital
May 17, 2018
Series A
$4.2M
Prime Venture Partners
Sep 1, 2017
Venture Round
$1.5M
Stellaris Venture Partners
MFine – Growth
MFine’s on-demand healthcare platform allows users to obtain virtual consultations and linked care programs from a network of hospitals. It was founded in 2017 by former Myntra executives Ashutosh Lawania and Prasad Kompalli, who were subsequently joined by Ajit Narayanan and Arjun Choudhary.
Over 3 million customers have used MFine services since its debut, with over 300,000 monthly transactions including medical consultations, diagnostic testing, e-pharmacy, and in-patient treatments. Mfine introduced a new layer to its virtual doctor consultations in October 2018 by connecting with laboratory and diagnostic services, giving its customers access to more than 700 diagnostic centres in 400+ locations throughout India. The company further has claimed to have a network of over 500 hospitals with 3000+ doctors.
Every month, over 100,000 people utilize MFine to schedule diagnostic testing. More than 6000 physicians, including some of India’s best, spanning 35+ specialities, work in over 700 reputable institutions. They assist millions of people in over 1000 locations around the country. Instead of aggregating doctors, it works with hospitals, allowing customers to consult doctors from their favourite hospitals through chat or video and receive prescriptions and basic care.
Since the outbreak of the COVID-19 pandemic and a rise in the uptake of digital health among Indians, MFine has grown 15% month on month. MFine is substantially investing in technology to make the telemedicine experience much easier and more effective for providing high-quality treatment.
During the Covid-19 in 2020, the firm claims to have provided teleconsultation for over a million people. To meet demand, the firm extended beyond cities to 1,000 villages throughout India, offering AI-powered self-assessment, long-term care programs for chronic diseases, and membership perks to both individuals and businesses.
MFine Merger
Mfine merged with LifeCell
MFine has merged with the diagnostic business of LifeCell International, as per the July 11, 2022, reports. After looking for numerous merger and acquisition opportunities for the past months, MFine has ultimately successfully merged. This merger has brought forth a new entity that will be termed as LifeWell.
As per the reports associated with the new, merged entity, LifeWell, it will stand as a full-stack digital health platform in the diagnostic space in contrast to the pure-play marketplace that MFine was. Besides, the joint entity has also raised $80 mn in a new round from OrbiMed. The total userbase of LifeWell has been combined to be estimated at over 6 mn users, which is growing at a rate of 100% Y-o-Y, revealed the companies in a joint press release. LifeWell is looking to serve more than 50 million users over the next 4 years.
This merger is the third major consolidation that the Indian healthcare/healthtech ecosystem has seen during the past couple of years. It was already seen that the unicorn Indian startup, Pristyn Care acquired Lybrate in a distress sale in June, and prior to that, we saw the merger of DocsApp and MediBuddy.
MFine Heart Rate Monitoring Feature
MFine unveiled its latest innovation by presenting the all-new heart-rate monitoring feature integrated with its app. MFine launched its heart-rate monitoring tool on its app on March 3, 2022, which is designed to help people keep a track of their heart rate without any external devices. As far as the latest news goes, nearly 700 people are using this tool of MFine to monitor their heart rate every day.
MFine Pulse
MFine developed an app-based SPO2 solution in early 2021, allowing users to monitor their oxygen levels without the requirement of separate equipment. Since then, the program has been utilized by over 250,000 people, with thousands more using it regularly. MFine will be adding heart rate and blood pressure monitoring to the product in the coming months.
As of April 2021, MFine has released MFine Pulse, a mobile application that can check blood oxygen levels with just a finger and a flash.
The technology, named MFine ‘Pulse,’ is now in beta testing for Android users and will be for iOS in a few weeks. Even though clinical studies for the tool are still ongoing, the tool looks to be promising, with an accuracy rate of 80%, according to a news release.
Thousands of customers are using the tool in the company’s Android beta rollout, generating hundreds of assessments every day that are put into machine learning techniques, which CTO Ajit Narayanan believes will increase the tool’s precision in the months ahead.
“For now, the goal is to make our SpO2 monitoring tool as accurate, if not more accurate, than pulse oximeters available at the pharmacy,” Narayanan said.
MFine Financials
MFine had last recorded Rs 70 lakhs in operating revenue in FY19, which surged by 7.3X to become Rs 5.12 crore in FY20. The total earnings of the company have been recorded at Rs 12.23 crore during FY20.
However, for the surge in its revenue, MFine also had to sacrifice a considerable amount of money because the losses of the company ballooned by 2.9X to become Rs 99.5 crore in FY20 from Rs 34.4 crore in FY19. The outstanding losses of the company were estimated in the FY20 fiscal to be Rs 140.2 crore.
MFine expenditures surged rapidly from Rs 34.4 crore that it spent in FY19 to become Rs 99.5 crore in FY20. The Prasad Kompalli-led company spent Rs 21.87 to earn a single rupee during FY20.
The losses for MFine further increased to Rs 102.7 cr in FY21, while its operational earnings went on to become Rs 12.9 crore during the same fiscal. The expenses of MFine were registered at Rs 116 crore.
The platform includes a sophisticated web of hundreds of machine learning algorithms and techniques across vision, hearing, and language processing modalities, allowing the virtual doctor to interpret data from numerous sources and propose the best next actions to the doctor.
According to Kompalli, the current problem is scaling innovation now that the prior hurdle of convincing people to switch to digital healthcare has passed. “We’re now facing innovative hurdles, such as how quickly we can scale up the ideas we made in the mobile and AI sector.”
In addition, the corporation is putting a lot of money into the platform’s AI capabilities.
They are working on inference capabilities to diagnose based on symptoms, patient history, and other data provided during the consultation, as well as computer vision capabilities to scan and automatically digitize diagnostic papers and interpret symptoms. Skills are being considered, such as determining the type of infection based on the sound of a cough, among other things.
MFine Layoffs
The Indian companies are seeing a spike in layoffs. MFine too announced its share of employee layoffs, where the company has laid off around 50% of its workforce, as of May 21, 2022. The BEENEXT-backed company has done away with 50% of its total workforce, and as per reports from close sources, a considerable chunk of the employee belongs to the operations, product, and marketing verticals. The latest layoffs were done, as per the sources, to reduce burn and extend the runway for the company. Source also claimed that the layoffs can go up as high as 70%.
Protests began within 2 days of the announcement of the MFine layoffs. Over 100 of the company’s employees started gathering outside the MFine Bengaluru office, demanding their full salaries for the month of May 2022, and an early release of their full and final settlement. People also claim that MFine has laid off the employees due to its inability to pay their salaries. The company has allegedly run out of funds. According to the employees, the pay cycle of MFine is from 20th to 20th, and they have served a full month that way and should be paid in full too. They were expecting an appraisal, added the employees, and had no idea about the company’s financial condition. The company, which had earlier announced to pay the employees 20 days’ salary for the month of May and said that it would credit the rest amount including that of the notice and period, and have their full and final payment settled, has now been pressurised by the employees to make the whole procedure fast and to credit the full month’s salary of May. The employees are also apprehensive about their salaries and mentioned that out of 3 offices, MFine has already closed 2, where only 1 office is currently operational, which might also be closed without clearing their dues.
Previously, Vedantu, Meesho, Cars24, Unacademy, and more have already laid off a considerable amount of their workforce due to the unstable financial grounds that they are standing on, and the fear of an impending recession.
MFine – Future Plans
MFine intends to treble its investment in Machine learning and artificial intelligence, mobile engineering, and device integration with this cash. Aside from that, it plans to grow its hospital network across the country and scale up newly released services like prescription delivery, preventative health screenings, and diagnostic testing.
FAQs
When was MFine founded and who founded MFine?
MFine was founded by Ashutosh Lawania, Prasad Kompalli, Ajit Narayanan and Arjun Choudhary in February 2017.
How is the MFine funding?
Looking at the MFine funding, the company has raised a funding more than $94 mn to date, as of July 2022.
How does MFine make money?
Commissions from client consultations, lead-generation fees from hospitals, and corporate tie-ups are the main sources of revenue for the firm. It also has partnerships with local hospitals to provide accessible and dependable medical treatment.
What is the use of MFine?
Mfine is an AI-powered on-demand healthcare startup that gives customers access to online appointments and hospital-based linked healthcare.
Which companies do MFine compete with?
Mfine’s top competitors include SeamlessMD, Happytal, Helium Health, MediBuddy, Pristyn Care, Doctor Insta, and Ferrum Health.
Has MFine been merged?
Yes, MFine, which was looking for a merger, has finally merged with LifeCell’s diagnostic unit to bring about a joint entity LifeWell, as per the reports dated July 11, 2022.
The COVID-19 pandemic has had impactful destruction worldwide. However, it has helped e-commerce market sales soar to great heights. As per recent reports, the Global E-commerce market is expected to cross the $5.5 trillion mark by the end of 2022. The growth rate of the market is expected to rise to 24.5 per cent by 2024.
Standing in the e-commerce industry isn’t everybody’s cup of tea. Big companies, such as Amazon, Flipkart, and Sephora have captured 60-70 per cent of the market. When it comes to customer acquisition, this sector has cut-throat competition. Hence, it’s essential for every e-commerce website/app to have a personalized marketing strategy – for a better user experience. In this post, we have talked about eCommerce personalisation and how to employ it to increase conversion rates.
Ecommerce Personalisation is a technique that furnishes brands/businesses with a unique personalized marketing ideology. The marketing strategies are entirely based on how users interact with the brand – to allow an ultimate shopping experience.
eCommercepersonalisation is in real demand at the moment. And that’s because of the perfect utilisation of data sources. Depending on the order history, user search, customer location, browsing data and user-generated data, the brand uses unique personalisation to build a top-notch customer experience.
The primary motive behind these personalisations is to show customers what they want to see and when they want it. So, customers get the relevant recommendation based on their preferences. All these undertakings are monitored using AI-based personalised software.
How Ecommerce Personalization Can Help You Increase Conversion?
Unlike a physical store, increasing the conversion rate in an online store is a difficult task unless you know what customers need. In a physical store, you have a chance to influence the mind of your customer by communicating. However, in online mode, it’s not happening. Thus, eCommerce Personalisation offers the audience every possible thing they would wish for.
With the user-generated tool, the brand understands the interest of the audience and estimates their responses. After all, every shopping brand seeks more information to provide a better shopping experience the next time.
Customers like to visit places where they get a user-friendly environment and where they are taken care of. So, the only way to make all of these things possible is personalisation.
A survey report provides the data, facts and stats that confirm – personalisation helps increase conversion rate. Almost 73% of the people prefer a personalized shopping experience. And, almost 90% of them accept that personalisation influences their right purchasing judgment.
Ecommerce Personalization Ideas
Here are some of the ideas on which Personalisation works:
Recommend the latest viewed products
It happens quite frequently that users might be interested in a specific product, but they forget to add it to the cart. Thus, this recommendation strategy will help customers start their shopping at the place where it ended.
Example of recently viewed products
Personalized product recommendation
Along with the previously searched product, you may recommend related products to the consumers. Personalizing product recommendation is one of the widely used eCommerce personalized ideologies. As per the report by Barilliance, personalized product recommendation generates up to 31% of the total revenue of an e-commerce site.
Example of related products
Create a personalized best-selling product list
You may create some sort of best-selling products list based on the user’s interest. It will act as a quick recall of the product they wished to buy earlier. This increases the chance of a conversion.
Allow UGC to work accordingly to help visitors
UGC works on the FOMO (fear of missing out) principle. It displays unique products that are used in daily life. Hence, creating a fear of missing out on the environment. It influences the customer’s mind that they might buy this product so that they don’t miss something.
Personalize the home page with recent searches
As mentioned earlier, Amazon uses this homepage personalisation technique to boost customer acquisition. It bestows an easy-to-use interface where consumers can find products of their kind on the home page.
Carry out an automated personalized email campaigns
Email campaigns are one of the primary steps to building a powerful user channel. It keeps you ahead of your competitors. Automated personalized email campaigns keep on reminding the customer about your assistance. Thus, increasing the chance of a conversion.
Example of cart abandonment email
Offer category-specific promo codes
Promo codes have always been a customer favourite part. It attracts them to certain product categories. Once you issue these category-specific promo codes, you may either send in an email or a pop-up message to keep your user up-to-date.
Example of promo code
Seek a customer’s feedback request
One of the most effective ways to know your customer requirements is to request customer feedback. It helps the brand improve personalisation techniques for that particular user.
Example of customer feedback
Show pop-ups considering the previously viewed products
Pop-up ads should always be the first preference while personalising a website. For instance, if the user is a first-time visitor, the pop-up will encourage them to subscribe and avail discount on the first purchase.
Example of Ecommerce Personalization
Still, confused with the principles and working of E-commerce Personalisation? Below listed are a few examples to assist you further for a better understanding.
Amazon
Amazon is the father of all eCommerce personalisation companies. Once you click on the app or website of Amazon, you’ll be redirected to the home page. There, you’ll find numerous personalized product recommendations.
Amazon automates all the data of your phone and recommends the products you recently enquired about. It uses search data, recent purchases, locations, and other data to provide particular recommendations.
If you wish to conquer the eCommerce sector, you should consider Personalization. Ecommerce personalization keeps your user engaged, provides a user-friendly experience, and increases conversion.
Personalization in eCommerce is vital as it ensures customer acquisition. Besides, it not only helps you stand out from your competition but helps build grounded/human-like connections with the buyers. It also furnishes customers full control, improving the user experience. This, in turn, boosts conversion rates!
FAQs
What is eCommerce personalization?
Ecommerce personalization is when a company displays the product to the consumers based on demographics, intent, preferences, browsing history, previous purchases, and device usage.
What is an example of personalized marketing in eCommerce?
When an eCommerce store recommends your products based on your interest, location, and browsing data.
What if, you are told that in near future surgeries will be performed by Machines. Yes, machine learning has advanced rapidly that in near future it will be possible to perform medical surgeries with minimum or no interventions by a Physician. Machine learning is widely used in healthcare industry in 2022.
When we hear AI or machine learning the first thing that comes in our mind is Robots but machine learning is much more complicated than that. Machine learning has advanced in every possible field and revolutionized many industries such as healthcare, retail and banking. In this article, we will talk about how machine learning is bringing a change in the healthcare industry. So let’s get right into the business.
Machine learning is an application of AI that provides the system with the ability to learn and improve from experiences without being programmed. The primary focus is to allow the computers to learn automatically without any human intervention or assistance. The process of learning begins with observations of data and finding patterns in data and making better decisions in the future. Machine learning has started making it place in India.
Machine Learning in Healthcare
The Healthcare industry has seen many advancements, but machine learning is one such advancement that has enhanced the performance of healthcare businesses. Machine learning has advanced a lot but the best machine learning tool in healthcare industry is a doctors brain. Many physicians worry that machine learning will dominate the healthcare industry.
Machine learning should be focused on how it can be used to augment patient care and employed as a tool by physicians to improve clinical use. Machine learning can never replace physicians because even if it reached supremacy, the patient always needs the human touch and caring of a physician.
How Machine Learning Is Used in Healthcare?
Machine Learning is taking turns and has entered into various industries and it looks like its not going to stop at any moment. It has also started showing its caliber in the Healthcare industry. Some of the ways it is used there are:
Identifying Disease and Diagnosis
Scientists are already working on machine learning models that predict disease or early diagnosis of disease and illness. A UK based technology startup feebris is working on artificial intelligence algorithms for precise detection of complex respiratory conditions. MIT’s Computer Science and Artificial Intelligence Lab has developed a new deep learning-based prediction model that can predict the development of breast cancer in advance up to five years.
Robotic Surgery
The application of robotics in healthcare is rapidly growing since it began in 1980. Robots performing surgery still might sound untrustworthy to many but in near future, it will be commonly used in surgeries. Robotics is also used in hospitals to monitor the patients and alert the nurses if there is human interaction required.
The robotic assistant can locate the blood vessel and draw the blood with less pain and anxiety for the patient. Robots also prepare and dispense medications and vaccines in pharmacological labs. In large facilities robotics are used as a cart to carry medical supplies. Speaking about robots replacing humans is not happening anywhere soon, robotics can only assist the doctors but can never replace them.
Medical Imaging Diagnosis
Medical imaging diagnosis is a process or technique in which visual representation of tissue or internal parts of organs are created to monitor health, diagnose and treat diseases. It also helps in creating database of anatomy and physiology. Surgical interventions can be avoided if medical imaging technology like ultrasound and MRI are used.
Uses of Machine Learning in Healthcare Industry
Machine learning algorithms can rapidly process massive amount of medical images and they can be precisely trained to identify the details in CT scans and MRI’s. A deep learning team from US, France and Germany have developed algorithm that can diagnose skin cancer more accurately than a dermatologist.
Pros of Machine Learning in Healthcare
More and more healthcare companies are choosing Machine Learningbecause pf its benefits. Some of the benefits are:
Patterns Are Easily Identified
A great ability of machine learning is that it can identify patterns and data precisely which might not be possible by a human. It can process massive amount of patterns and data rapidly with ease. With new innovation all of these are possible.
Smart Health Records
Maintaining health records is an exhaustive process so machine learning is used to ease the process and reduce the time and efforts required for maintaining health records. Machine learning in today’s world is working on cutting edge technologies for maintaining smart data records.
Minimum Human Intervention
Machine learning adapts overtime by learning from patterns and data. The primary benefit of machine learning is that it requires minimum intervention by humans and it can perform surgeries with ease.
Cons of Machine Learning in Healthcare
There is also a hesitation as well because with benefits Machine Learning has some cons as well. Some of them are:
Data Acquisition
Machine learning adapts through patterns and data sets and it requires a massive data sets and patterns to train its algorithms. The data should be precise and of good quality.
Take Time to Learn and Adapt
Machine learning requires enough time for its algorithms to learn and adapt to the patterns and data so that it can deliver accurate results. It requires additional computer power to function.
High Error-Susceptibility
Machine learning is highly susceptible to errors, it requires massive amount of data and if it is not provided with sufficient amount of data it may not function properly. Any inaccurate data fed to the machine may end up in undesirable result.
In-Med Prognostics Launches Neuroshield
InMed Prognostics Logo
One of the prime example of Machine Learning in the health industry is how In-Med Prognostics, a health tech company developing AI based brain health diagnostic and prognostic tools, launched NEUROShield, a cloud-based Clinical Decision Support Tool for neurological disorders. The NeuroShield technology uses pattern recognition and deep learning for the development of clinical biomarkers for early prognosis and differential diagnosis.
NEUROShield, powered by state-of-the-art AI, utilizes 3D based MRI images to their full potential by extracting data and providing volumetric analysis for the brain and its various structures. Use of cutting edge, AI technology enables them to perform analysis, on both Indian and Caucasian brains, thus unlocking a global scalability potential for their platform. AI is increasing innovation in the enterprises.
Future of Machine Learning in Healthcare
The development in machine learning will be able to automatically detect most of the diseases in its early stage. It will also increase the efficiency and accuracy in disease detection to reduce the burden on doctors. AI and Machine Learning will revolutionize the future healthcare industry.
Machine learning has advanced rapidly in every field such as navigation, business, retail, and banking but progressing in the healthcare industry is difficult because of the limited availability of data and lack of highly skilled scientists. Machine learning still requires improvements and several factors need to be improved.
Conclusion
Machine learning in the healthcare domain has become more popular and widely used in the healthcare industry. ML is helping patients and clinicians in many different ways by making their work easy. Some of the most common applications of machine learning are automating medical billing, clinical decision support, and the development of clinical care guidelines. There are a lot of applications of machine learning that are under research and development. In the future, we’ll be seeing a lot of applications of ML in the healthcare sector getting implemented and making the lives of humans easy.
FAQs
What is ML healthcare?
Scientists and researchers are using machine learning (ML) to churn out a number of smart solutions that can ultimately help in diagnosing and treating an illness.
How is machine learning used in medical diagnosis?
Studying physiological data, environmental influences, and genetic factors allow practitioners to diagnose diseases early and more effectively. Machine learning allows us to build models that associate a broad range of variables with a disease.
What is machine learning in medicine?
Machine learning (a subset of artificial intelligence) plays a key role in many health-related realms, including the development of new medical procedures, the handling of patient data and records, and the treatment of chronic diseases.
What are the benefits of AI in healthcare?
Integrating AI into the healthcare ecosystem allows for a multitude of benefits, including automating tasks and analyzing big patient data sets to deliver better healthcare faster, and at a lower cost. According to Insider Intelligence, 30% of healthcare costs are associated with administrative tasks.
How is Machine Learning used in hospitals?
Machine Learning analyzes data throughout a healthcare system to mine, automate and predict processes. It has been used to predict ICU transfers, improve clinical workflows and even pinpoint a patient’s risk of hospital-acquired infections.
Company Profile is an initiative by StartupTalky to publish verified information on different startups and organizations. The content in this post has been approved by Enthu.ai.
Conversational analytics is the concept of extracting useful data from human speech and making analysis/interpretations using AI/ML. As technology is advancing exponentially, so are the great minds of entrepreneurs. Tushar Jain realized that there is still less scope outside in automating the manual process of sales people.
He got his Eureka moment, and established an amazing product named ‘Enthu’. Enthu (as a product) was conceptualized and built by the entrepreneurial and technical minds of Tushar Jain and Vishal Verma.
Conversation analytics is a costly technology, thus limited to only a few. Enthu’s vision is to make conversation analytics/speech analytics platform affordable to businesses at a reasonable rate with important feature. Enthu is a SaaS based conversation intelligence platform that turns customer calls into actionable insights.
StartupTalky interviewed Tushar Jain (Founder of Enthu.ai) to understand the Conversation analytics industry and know about Enthu.ai Startup Story.
So, let’s walk through the Startup Story of Enthu.ai and delve into everything about Enthu’s founder, business model, startup idea, products, revenue model, and more.
Enthu is a SaaS-based conversation intelligence platform that turns customer calls into actionable insights. It automates the ability to listen to every customer interaction and drive agents’ performance by identifying the behaviors that impact outcomes.
Enthu is aimed at improving contact center performance by delivering highly effective, scalable, and usable conversation analytics. The core of the platform is analytics, where each call is analyzed for call moments and reports can be pulled out for QA analysis. Enthu can completely analyse the call interactions, extract actionable sentiment and interaction insights, and in this way, it helps to streamline the workflows.
It is a horizontal play, which means Enthu can be easily deployed across business functions, be it the revenue side (like sales, customer success etc.) or the margin side (like customer support, call quality monitoring, rep training & coaching, recruitment operations etc.).
Create customized call moments with Enthu
Products of Enthu.ai and how does Enthu.ai work?
The product (Enthu) integrates with the VoIP platform which calling teams use. The call feeds are automatically picked by Enthu and analyzed.
One of the important aspect here is that the product is 100% customizable i.e. the user can replicate their calling scripts/themes in the system, create teams/agents and assign custom feedback forms. The core of the platform is the analytics where each call is analyzed for call moments and reports can be pulled out for QA analysis.
Enthu Call Analysis
Enthu.ai aims to help the managers gain a complete awareness of their customer service operations, which will let them run coaching for their agents.
Suppose a company would want to run a Christmas campaign where they would offer their products at a discount. Here, they need to make relevant calls that the agents would dial. In such situations, the call centre managers were rendered helpless at the end of the day earlier. However, now they can now evaluate the calls and check whether the pitching was right and all the points of improvements that they bring to the process. Enthu.ai would help them define the manual script where they would not have to listen to random calls anymore. The Enthu software would instead help them process all the calls and provide detailed reports or conversation analyses.
Enthu.ai – Market/Industry Details
Conversation Analytics Platform & Speech Analytics is the domain of Enthu.ai.
As per a report by Mordor Intelligence, the speech analytics market worldwide was valued at $1.34 billion in 2019, and is expected to reach a value of $4.38 billion by 2025. That’s a CAGR of 21.6% over the 5-year period between 2020 and 2025.
While North America is still the largest market, Asia Pacific is the fastest-growing market, probably because of the high concentration of call centers in the region.
Tushar Jain is the Founder of Enthu.ai. Vishal Verma is the Technical Co-founder of Enthu.ai
Tushar Jain, Founder, Enthu.ai
Tushar Jain (Founder, Enthu.ai)
Tushar Jain is an Engineer, who has completed an MBA from NMIMS. He has over 9 years of corporate experience working in brands like McKinsey & Company and HCL Tech. He has also worked in startups like Jugnoo Technologies, where he worked as Head of Marketing. Tushar was also the Head of Marketing at Kays Harbor. After that, he founded OnPage Champ. He led the entrepreneurial journey since January 2019, when he started working on his 1st product – OnPage Champ. He then founded Enthu.ai in July 2020.
Vishal Verma (Head of Technology, Enthu.ai)
Vishal joined us as an employee of Enthu.ai in March 2020 (for OnPage Champ). He has a very rich experience in servers and algorithms. He displayed exemplary leadership, and problem-solving capabilities and was instrumental in building the crawling engine of OnPage Champ.
As they decided to start working on Enthu, Vishal shared his vision about building Enthu.ai and offered to join as a technical cofounder for Enthu. That’s how Vishal boarded with Tushar.
Vishal’s role in building Enthu.ai was exemplary. He guided the team and ensured that they launched the MVP for Enthu in just 20 days, and by the end of the first month, they were together pitching Enthu to real customers. Vishal left the company in December 2021 and then began to work as an IT Consultant.
Gaurav Mittal is another Co-founder of Enthu.ai, who is serving the position at Enthu.ai since May 2021.
Enthu’s work culture is more of a decentralized organisation. At Enthu, individuals are motivated to take decisions irrespective of the outcome.
Its hiring criteria is simple –
“We are fast movers and we chose people who are independent thinkers and take ownership of their work” Says Tushar Jain, Founder, Enthu.ai
Enthu.ai – Startup Story
The idea for Enthu germinated while Tushar was trying to scale his other product OnPage Champ (the product is still active and has a user base of 2000+).
During the COVID lockdown, Tushar was trying to scale up the outreach team at OnPage Champ. The idea was – the team makes calls and converts the inbound leads that were generated on the website. His sales reps were working remote and there was no way he could quickly analyze what was happening on the calls, except going through the meeting notes or listening to the calls. Both these activities required a significant amount of time investment, something which he couldn’t afford.
In a way, he felt a lack of control over the feedback, coaching and training, that he should offer to the salespeople, basis the conversations they are making day in and day out.
At that moment, Tushar started looking for conversation analytics solutions in the market. There were a couple of great options, but all were heavily priced and targeted towards enterprises. Moreover, a majority of them wanted a prior commitment, either in terms of number of agents or annual contracts, something which he wasn’t ready to make. This was his eureka moment: to build a speech analytics platform that can cater to a wider audience (especially SMEs), irrespective of any restrictions.
There are a number of contact centers in Chandigarh and he started talking to founders and operation managers. The idea was not to pitch the solution but to understand the following-
How do they manage the call quality?
What are their pain points?
How frequent are the pain points and what they are doing to solve it?
I strongly recommend you to read “The Mom Test” if you want to learn how to take customer interviews – Says, Tushar
Based on these interactions with people, Tushar realized that monitoring call quality is still a manual process across majority of the contact centers, and that there’s a lot of scope of automating this labor-intensive process. That’s when Tushar along with Vishal, started working on the MVP for Enthu.
Tushar (founder of Enthu) was looking for an adjective that has a close association with people who sell on calls. Being enthusiastic about one’s product/service is the first step to success when it comes to sales. That’s how the slang ‘ENTHU’ was determined.
Enthu.ai
Enthu.ai – Business Model and Revenue Model
Enthu works on per agent per month model, with no annual or minimum rep commitments. It offers a 14-day free trial during which it runs a pilot for the customers to showcase the value of speech analytics and conversational AI.
The base plan for Enthu starts with $25 per agent, and that includes fixed number of transcription hours. It also offers custom plans depending on calling needs and volume.
Enthu.ai was initially bootstrapped before it raised a $15 mn Pre-Seed round of funding led by Ankit Dudhwewala, and Appit Simple Infotek. Suhasini Dudhwewala is another investor of Enthu.ai
Date
Funding Round
Deal Value
Lead Investors
May 11, 2021
Pre-Seed Round
$15 mn
Ankit Dudhwewala, Appit Simple Infotek
Enthu.ai – Customer Acquisition
Via cold outreach and referrals, Enthu acquired a couple of customers since its inception. The customers are majorly contact centers and SaaS companies. It has already established the RoI of the product for its initial few customers.
“LinkedIn works best for us to acquire customers.”- Says Tushar
Enthu.ai – Advisors and Mentors
CallHippo, a leading VoIP provider is Enthu’s partner. CallHippo helped them to get lot of industry insights and mentorship.
Enthu.ai – Startup Challenges
Tushar felt that technology was one of the main challenging aspects, as the system had to be made accurate with an Indian English Accent. However, at the end, they were able to solve it and create an amazing speech analytics platform – Enthu.ai.
Enthu.ai – Future Plans
Enthu’s goal for the next 1 year is to work closely with its customers and identify more use cases for the application of voice analytics at contact centers and accordingly invest in the product.
FAQs
What is Enthu.ai?
Enthu.ai is a Chandigarh-headquartered conversational AI startup that was founded in 2020 by Tushar Jain and Vishal Verma, which is helping monitor and analyse the calls and extract valuable information to enhance call quality.
Who were the founders of Enthu.ai?
The founders of Enthu.ai are Tushar Jain and Vishal Verma.
The article is contributed by Biswajit Das, Founder – Brandintelle Services
Businesses & governments cannot do without AI/ML. Yet if we take it too seriously we may be misled, sometimes with very serious effects. But the reality is that in future, both governments & corporations may have to appoint AI/ML ombudsmen to check & control AI/ML algorithms.
We have all faced occasional inquiries from our respective Direct & Indirect Tax Departments pertaining to a past period – which suggest that we have evaded taxes. The notice further asks us to prove that we are not evaders by furnishing documents that we had already furnished years ago. These are the results of AI/ML algorithms which are run by Tax Departments on the vast amounts of data that they have aggregated. In most cases, they serve as irritants, forcing citizens to submit the same documents multiple times at their own time & cost.
Apart from the stress that this generates on semi-literate or otherwise challenged taxpayers, there is the odd case where the allegation by the algorithm can be of a more serious nature – without any justification. Repercussions of such AI/ML “activism” can be far more serious in-patients medical records as the following case shows.
In 2021, Wired magazine reported a case of a patient who was suffering from a chronic condition which caused her great pain. Although the situation was not critical, the medicines were clearly not working. And surgery was very risky. To alleviate her pain, her physician naturally regularly prescribed opiates as painkillers. for multiple years.
After many years, her physician recommended a hospital visit – for a second opinion as well as a possible alternate treatment. The patient visited & was asked to register as an in-patient for some examinations. She was accommodated & tests were conducted. Meanwhile, she ran out of her opiate painkillers & asked for a fresh prescription. This was a normal request as far as the patient was concerned – but it resulted in a deadlock situation. The hospital did not prescribe the medicine & nor did it give any reason. As soon as the tests were completed, they requested her to leave the hospital as they could not treat her any longer. Upset & perplexed, the patient went home & asked for an appointment with her regular physician. But she was in for a rude shock! Her physician refused to treat her. After much pleading, she was able to extract the reason – her identity was “blacklisted” as a substance abuser and on the basis of this, the medical profession was practically asked to boycott her. It took her many months to reverse the situation.
What had happened behind the scenes just before this period is interesting. The hospital had signed up to outsource its Hospital Management System along with Electronic Medical Records to a third party along with a group of regional hospitals & regional physicians. The third party managed to aggregate patient medical records from all the hospitals, & physicians into a data lake. And as is the custom today, built some “intelligence” into its Hospital Management System with AI/ML. The algorithm that was published had an inbuilt logic that apparently categorised all prescription opiate users as “substance abusers” if they used opiates for more than a certain (undisclosed) period! The Hospital Management software automatically “blacklisted” such patients & barred them from any medical treatment!
Current & future generations may rely on AI/ML as the ultimate decision-making tool. But in reality, AI/ML simply points to signs, trends & predictions all based on applied statistics (from the eighties & earlier!) which are applied to available historical data. This was not possible till the price-availability of computing & storage power crossed a threshold level – which happened in the last 5 years.
But here’s the thing: both data & algorithms are prepared by human beings. Therefore both are imperfect. And to make it worse, both data & algorithms are ‘opaque’ to end-users, making some victims & others perpetrators!
Yet we tend to treat the predictions & pointers as though they were the Gospel truth!
While these nudges & prediction techniques work in general, it can be fatally wrong at times. As the adoption of AI/ML proliferates, there will be a need to appoint regulators & ombudsmen who will have the right to examine & override decisions taken based on AI/ML algorithms.
With the drastic change in the world and its pace. Almost all the things went into modifications. With the uncertainty in the present environment, nothing can be assumed perfectly for the future. However, few things can be assumed with confidence based on the current situations being faced by everyone. The current situations are one of the greatest examples of uncertainty, yet they are examples of correctly done predictions in the year 2020.
With the current situations and changes noticed, it can be assumed that a more revolutionary period is going to arrive and will bring complete changes within the respective fields.
Let us have a slight look at a few predictions that can work in 2022
There are many predictions done for the year 2022 in each field. Despite the current circumstances, one can assume some uplifting scenarios to occur in 2022. A few of the basic changes that are predicted for the upcoming year are shared below:
1. Working from the office is not a compulsion anymore
Earlier, it was estimated that a good job is the one that is fixed and is done from the office. People used to look down on those performing work from home or had shifting work. The lockdown initiated work from home as the new norm. This will continue to be carried out in 2022, with a few more changes induced in it according to the time and phases. People will no longer be afraid to announce their jobs as remote work.
2. Health preferred over wealth
With the pandemic lingering over our happiness. The real lesson learned by everyone in the year 2021 is that health is more precious than any other asset. Hence in the future, everyone will be more attached to wellness and health programs rather than ignoring them like earlier. There can be new norms also created by the companies to ensure the proper health of their employees. The health and wellness programs are going to be in good limelight in the year 2022. The other reason to arrange those programs can be to help out certain people still in depression and coping hard with their griefs.
3. Preferred use of Online sources than traditional method
Earlier there was not much recognition for those working with online platforms such as YouTubers. The majority of the crowd used to consider them as side business only. However, after the changes induced by lockdown and the pandemic, there will be open recognition for those working on online platforms also. They already had a spike in their business, and this legacy will be carried out in the year 2022 also.
4. Online Conferences will be accepted
Zoom Logo
During the pandemic, it was impossible to make people gather in one room. Hence, people started taking the help of online platforms such as Google to meet, Zoom, etc. They allowed the meeting to happen but in a new way. In the year 2022, the same procedure will be followed. There can be some new terms proposed for it, but it will still stick as a general routine for many people.
5. Different solutions for same old issues
We all know about the scarcity of food which is going to be faced by all of us in 2022. Hence to work with that situation, different food times will be included in regular diets such as aquatic animals and plants. Along these, similar situations will be required to have a new solution for the survival of the human race. There will also be the addition of vaccination drives concerning other diseases.
6. People more opening up to their choices
Working in a stressful environment will eventually have a great impact on the work done by the employees. The pandemic taught people how to deal with different kinds of people easily by setting up examples now and then. There will be more space required by employees while working. Any intrusion in it will cause a backlash by employees. Employees will no longer be threatened by the employer and will be ready to stand against wrong. Employees will also no longer feel the need to stick with one employer only if feeling unsatisfactory.
7. The offline world will need to compete with the online world
The graph shows the E-commerce share of global retail sales from 2015 to 2021
Online Retailer stores such as Amazon and Flipkart are giving hard competition to offline retailing stores. In 2022, there will be a need to create new strategies and implement different methods for offline stores to work. Not just about a retail store. Every offline store is facing a hard time due to online platforms. Hence, in the year 2022, we will be seeing the hardships faced by offline stores against online ones. The hardships will be more complicated as the online platforms are getting updates daily. These will eventually have an impact on the economy of the country.
8. Cryptocurrency will be the new currency
In the year 2022, cryptocurrencies can be estimated to be used in local markets also. They can be on the verge of exchanging local currency. There will be more job opportunities found in the field of cryptocurrency and many people will try out their luck in it. In the year 2022, various programs can be initiated to make cryptocurrency accepted by the world on a great scale.
9. More interference from AI in workplaces
The use of technology for the betterment of people and easy handling of work will set a new mark in 2022. There will be more introduction of automated plans in factories to reduce the manufacturing cost and to have more production in less amount of time. It will be a revolutionary period for factories. However, this will eventually lead to fewer jobs being given to people as more work will be done by machines only.
With the changing world, many things have changed. And in the future, many things will continue to change. As we reached the mid of 2022, few predictions about the rest of the year can be made easily. The essential changes that will be followed up in the next year and the things that will still be going on the same level for next year also. Some of them are listed above.
FAQs
What jobs will be in demand in 2022?
There will be many jobs in demand once the normal circumstances get back in the world. Some of them are system analysts, blockchain engineers, product managers, full-stack developers, etc.
What new changes can be accepted in 2022 after the pandemic?
Changes like contactless delivery, cashless payments, etc. can be defined as new norms after the pandemic.
Does one need to prepare for 2022 amid a pandemic?
One needs to be well prepared for the future irrespective of its uncertainty. Planning is an essential point to fulfill before starting any great thing.
Company Profile is an initiative by StartupTalky to publish verified information on different startups and organizations. The content in this post has been approved by Tempus.
Technology is a vast field and in the field of science, technology is getting advanced rapidly. Biotechnology is a department of applied science that uses living organisms and their products to produce various processes. It is a very important part of the industry sector in the economy.
Tempus is a technology company which has created the world’s biggest library of molecular and clinical data. It is making accurate medicine through the power and the promising nature of data and artificial understanding. Read the Tempus success story below.
Tempus – Company Highlights
Company Name
Tempus
Headquarters
Chicago, IL, US
Industry
Analytics, Artificial Intelligence, Biotechnology, Healthcare, Medical, and Software
Tempus built an operating system to make information accessible and beneficial for physicians, researchers and patients. The mission and the vision of the company is to change the world in the field of medicine. It enables physicians to deliver personalized attention to everyone’s diagnosis. Tempus also works with partners to encourage development and discovery.
The company started with the concept of curing patients for a variety of diseases, starting from cancer to depression-like disorders. It is currently also curing Covid patients. The founder of the company had his own personal reasons for founding Tempus.
‘My wife was diagnosed with breast cancer about five years ago, and I was amazed how little data was actually used as a part of her therapy, largely because our system makes it hard for doctors to access data when making real-time clinical decisions,’ Lefkofsky said. ‘It became clear to me that I needed to try and tackle this problem, and I founded Tempus soon afterwards.’
Tempus – Founder
Eric Lefkofsky, Founder & CEO, Tempus
Eric Lefkofsky is the founder and the CEO of Tempus. Currently, he is the Chairman and the Co-Founder of Groupon, Lightbank, and Lefkofsky Family Foundation. At Groupon he previously served as the CEO of the company which is an e-commerce marketplace. He is also the founder of MediaBank. He graduated from the University of Michigan.
Tempus – Business & Revenue Model
‘We try to infuse as much data and technology as we can into the diagnosis itself,’ Lefkofsky says.
The Tempus business model lies in the fact that they do not only focus on cancer but also focuses on other programs which include cardiology, diabetes, mental health or any other infectious or deadly disease. The company offers a service that matches eligible patients to clinical trials. Tempus also licenses de-identified patient data to other players in the oncology industry. Tempus offers a service for the psychiatrists to use a patient’s hereditary information to determine the best treatments for major depressive disorders.
The main Tempus labs revenue model lies in sequencing the genome of cancer patients’ tumors. It helps the doctors to decide which treatment is more effective for which patient.
Tempus has raised a total funding of $1.1 Billion. Tempus is funded by 10 investors. It has got 5 lead investors. Baillie Gifford is the most recent investor.
Date
Transaction Name
Money Raised
Lead Investors
December 10, 2020
Series G
$200 million
Google
December 10, 2020
Debt Financing
$250 million
–
March 13, 2020
Series G
$100 million
–
May 30, 2019
Series F
$200 million
Baillie Gifford
August 29, 2018
Series E
$110 million
Baillie Gifford
March 20, 2018
Series D
$80 million
T.Rowe Price
September 25, 2017
Series C
$70 million
New Enterprise Associates and Eevolution
April 17, 2017
Series B
$30 million
–
November 22, 2016
Series B
$10 million
–
June 20, 2016
Series B
$10 million
–
Tempus – Growth & Future
‘We couldn’t be more thrilled with our progress to date, and we’re honored to be surrounded by world-class investors, collaborators, partners and an incredibly talented team here at Tempus,’ Lefkofsky said in a statement.
Tempus focuses on the analysis and the gathering of clinical and molecular data. The company considers itself to be the most comprehensive data set in the industry. Tempus believes that it has been only possible with the help of its clinical partners. The company has got relationships with various cancer centers, physicians and health systems. Tempus is growing in such a way that now the company’s technology is affecting 1 in 4 cancer victims in the country.
Tempus also recently announced its collaboration with A2 Biotherapeutics to develop a (CDx) companion diagnostic test. It is also looking forward towards the development of more CDx tests for A2’s different clinical development programs.
The top Tempus competitors COTA, Flatiron Health and Fabric Genomics.
COTA is one of the biggest competitors of Tempus. It is headquartered at Boston, MA, USA and was founded in 2011. It works in the Healthcare Technology field.
Flatiron Health is perceived as one of the biggest rivals of Tempus. It is headquartered at New York, NY, USA and was founded in 2012.
Fabric Genomics is also one of the top competitors of Tempus. It is headquartered at Oakland, California, USA and was founded in 2009.
Conclusion
Tempus is making precision medicine a reality through the power and promise of data and artificial intelligence. With the world’s largest library of clinical and molecular data, and an operating system to make that data accessible and useful, we enable physicians to make real-time, data-driven decisions to deliver personalized patient care, and in parallel, facilitate discovery, development, and delivery of optimized therapeutic options for patients through distinctive solution sets.
FAQs
What is Tempus?
Tempus is a technology company that has built the world’s largest library of clinical and molecular data and an operating system to make that information accessible and useful for patients, physicians, and researchers.
What is Tempus testing?
The Tempus|TO test compares a patient’s tumor molecular data to a large internal database of annotated tumor data to identify a likely diagnosis that may impact standard of care therapy decisions, clinical trial enrollment, and reimbursement for therapies.
Who is the founder of Tempus?
Eric Lefkofsky is the founder & CEO of Tempus.
When was Tempus founded?
Tempus was founded in 2015.
What type of sequencing does Tempus perform?
Our labs sequence both DNA and RNA from tumor samples as well as matched DNA from normal samples. Sequencing options include a targeted panel of 648 genes (at 500x coverage), whole exome (at 150x coverage), and whole genome (at 30x coverage).
What is Tempus’ turnaround time for test results?
Tempus results can be expected 9-14 days after samples are received (both blood and tissue). Sequencing will not begin until all required specimens are received.
Who can order the Tempus test?
Clinicians treating patients who suffer from depression, anxiety, or other psychiatric conditions can order a Tempus test.
Sushree Sangeeta Behera
