This Kota Based Startup Uses AI For Affordable Smart Healthcare Solutions
“MedCords is India’s first holistic healthcare ecosystem, connecting patients, doctors, pharmacies, and laboratories for seamless healthcare access.” Setting up video consultation calls for his father – a doctor by profession after he suffered a slip-disc problem, Shreyans made sure that his father’s patients continue to receive medical services. This incident of 2014 prompted Mehta to launch MedCords along with Nikhil Baheti and Saida Dhanavath. The Kota-based company, MedCords, founded in 2016, is said to be India’s first holistic healthcare ecosystem, connecting patients, doctors, pharmacies, and laboratories for seamless healthcare access. Talking to Analytics India Magazine, Shreyans Mehta, Co-founder, MedCords, said: “Since the past five years we have been working diligently to solve the problem of accessibility, cost, and quality of healthcare and worked on making healthcare accessible, affordable and efficient for all by integrating it with data-science.” The company, with a network of more than 25,000 medical stores and 5000 plus specialist doctors, is providing healthcare facilities to more than 30 lakh families across 13 states. Aayu app and Sehat Sathi are their flagship products. Users can browse medical businesses, order medicines, consult doctors and store reports for doctor’s references in the future via Aayu app. Additionally, the company offers an Aayu Card subscription plan to let users consult doctors roughly for Rs.50 for the whole year. With the Sehat Sathi app, the chemists can help patients get online consultations with doctors, order drugs for their medical stores from distributors and sell the Aayu card. They get a commission paid for each card they sell. “In order to simplify patient records, we have integrated digital records with artificial intelligence that can facilitate more than 10,000 consults with average prescription writing time of less than 1 minute,” said Shreyans. “We are planning to expand all over India and are aiming to reach out to 50 million users by March 2022 and 1 lakh pharmacies on MedCords by December 2021”Shreyans Mehta MedCords organises a family’s medical history consisting primarily of unstructured data such as images and pdfs of prescriptions, X-rays, MRIs, as well as structured text data such as symptoms reported by users. Utilising InceptionV3 deep learning model architecture for data extraction and training image datasets on Yolov3 architecture, the company presents an organised medical history to the users in private mode, thereby ensuring privacy as well. Mehta said: “From the test report results, our OCR engine is able to extract the abnormal test values and provide preventive recommendations. This is unique in the Indian healthcare ecosystem.” Customer service bot – AayuBot, available in the app, is based on Dialogflow to handle user queries in the app and assure the fastest possible response time. Again, the company’s fraud detection engine is constantly fed with daily transactions on the platform, allowing it to detect fraudulent transactions and determine the authenticity of app users. “In the coming future, we’ll be building rich predictive analytics to do a health risk assessment and personalise the healthcare delivery experience for our active user base,” added Mehta. MedCord’s Tool Stack Python, GoLang, AWS & GCP services/APIs, Docker, MongoDB Cloud, ElasticSearch, Redis and Aerospike.App side (customer-facing) technology is based on Kotlin, Angular & React.The data engineering platform uses Apache Spark and Hadoop for processing data sets. High-uptime, data security and privacy are the major focus areas outlined by the company. “We’ve built a deeply connected yet decoupled ecosystem where medical data sharing between family members, their doctors, as well as nearby medical stores is smooth and secure at the same time,” explained Mehta. Medcords is currently associated with the Government of Rajasthan for providing last-mile accessibility of medical resources during the nationwide lockdown. The company witnessed a surge in demand for medical assistance, thereby requiring the team to work 24/7 till now. Medcord’s platform saw a jump in consultation with food consultants and dieticians. Travelling over 75,000 km in the villages of Rajasthan, UP, MP and Bihar for two years, meeting people in semi-rural and rural pockets provided them with a better understanding of the industry. After raising around $4 million in funding so far, the company is aiming to raise $8 to 10 million in the next six months to scale the platform in the Hindi-speaking states in India. It is in the process of expanding its local pharmacies network across India to digitise and become a part of a unique hyper-local delivery model. “Another aspect of our future plan is to set up a robust data-science platform to determine disease-symptom relationships and identification of health risk patterns amongst family members. We are also heavily investing in artificial intelligence and machine learning to make the business model more seamless,” concluded Shreyans Mehta.
“MedCords is India’s first holistic healthcare ecosystem, connecting patients, doctors, pharmacies, and laboratories for seamless healthcare access.”  Setting up video consultation calls for his father – a doctor by profession after he suffered a slip-disc problem, Shreyans made sure that his father’s patients continue to receive medical services. This incident of 2014 prompted Mehta to […]
The Kota-based company, MedCords, founded in 2016, is said to be India's first holistic healthcare ecosystem.
["video processing ai"]
["machine learning", "artificial intelligence", "AI", "ML", "video processing ai", "RAG", "Ray", "Aim", "deep learning", "analytics", "predictive analytics"]
["AI", "artificial intelligence", "machine learning", "ML", "deep learning", "analytics", "Aim", "Ray", "RAG", "predictive analytics"]
Kumar Gandharv, PGD in English Journalism (IIMC, Delhi), is setting out on a journey as a tech Journalist at AIM. A keen observer of National and IR-related news.