Banking On 10 Mn Patients, $36 Mn-Funded Big Data Analytics Startup Innovaccer Is Aiming To Break Even By 2019
The global healthcare market is expected to touch $2 Tn in 2018, as per predictions by consulting firm Frost & Sullivan. Despite its unprecedented growth in the recent times, the healthcare sector is still largely dependent on outdated, inefficient methods of data collection and processing. Fighting these problems in the US is a three-year-old Indian startup: Innovaccer.
Striving to bring efficiency to the overall healthcare system, Innovaccer is a big data SaaS startup founded by Abhinav Shashank, Kanav Hasijaand Sandeep Gupta in 2014. The Silicon Valley and Noida-based company is focussed on helping healthcare organisations accelerate innovation by making powerful decisions based on key insights and data-driven predictions.
Its flagship product, Healthcare Data Platform, has been used by more than 10,000 healthcare providers, affecting the lives of over 10 Mn patients in the US, as of February 2018. The 500 Startups-incubated company, having clocked 400% YoY revenue growth within four years of its launch, is now leveraging the $9 Bn healthcare analytics market to evolve into a $100 Mn company.
During an engaging interaction with Inc42, co-founder and COO Sandeep Gupta shared some valuable insights into the startup’s initial journey and its plans to reach breakeven by 2019-end.
The Growing Necessity Of Structured Data Analysis And The Birth Of Innovaccer
Innovaccer was founded by three friends. While Abhinav and Kanav were batchmates at IIT Kharagpur, Sandeep and Abhinav met while working at diversified industrial manufacturing company Ingersoll Rand. It was during that time that Abhinav and Kanav got an opportunity to work on a data analytics project conducted by Wharton and Harvard University.
The project: a basic research of how large amounts of data (what we call big data) can be compressed and studied and the insights that can be derived from the same. The idea was simple: to leverage big data and machine learning to derive particular insights in different areas of interest and research and give the output in product form.
