What are the top 5 Data Science startups in India?

Without a doubt, data has emerged as the backbone for businesses, leading to the adoption of Data Science. Machine Learning models are used to prepare, organize, generate, analyze, and use data by the companies. Real-time analytics tools and specialized software are at the heart of Big Data & Analytics. Several Data Science companies have formed in recent years due to the market’s constantly expanding demand.

We will discuss the Data Science startups in India that are taking the market with fire.


Preksha Kaparwan, Saurabh Moody, and Arjun Sudhanshu founded a startup in 2015 to provide unique experiences by resolving real-time problems. They created Pulse, a tool similar to Google Analytics that takes care of big data Hadoop.


Former Google workers Jonathan Matus and Pankaj Risbood founded data analytics firms in 2013. They designed a platform to collect insights from sensor data from mobile devices. The platform’s technology is data-driven and AI-driven, which aids in the analysis of client data.


3LOQ was formed in 2014 by Sunil Motaparti and Anirudh Shah to provide data analytics for permeating large data. They provide NLP and machine learning frameworks for the Fintech industry, which they use to improve asset management systems and streamline customised communication in digital financial services.


Razorthink was formed in 2015 by Harsha Nutalapati, Barbara Reichert, Gary Oliver, Rupesh Rao, Murali Mahalingam, Dr. Nandu Nandakumar, and Tom Drotleff as a business AI solutions provider. The organisation uses automation, AI optimization, data science, and dynamic models to provide AI-based customer services, intellectual process automation, fraud detection, risk management, and business predictions, among other things.


Kunal Prasad and Krishna Kumar established a SaaS model for the agricultural sector in 2010. Data interpretation, weather foresight, financial analytics, geotagging, satellite monitoring, big data analytics, AI, and other services are available to farmers through the organisation.