Our Story

ScoreData was founded in 2014 on the premise that with the availability of large data sets and substantially cheaper compute power, memory and bandwidth, traditional AI systems had evolved substantially and could be used in new and innovative ways in the enterprise.  A significant impact of this evolution is that, for the customer-facing enterprise, human-written rules of engagement are being rapidly intuited from historical data sets in real-time or near real-time with machine learning. ScoreData’s co-founder, Vas Bhandarkar, who was an early employee, and co-founder of  two well-known AI powered companies, Remedy Corporation and Selectica, was fortunate to learn from their masterful co-founders.

With a great deal of experience of designing, developing and scaling companies “from scratch to IPO”, the ScoreData team got its first break building machine learning models using very large data sets at one of the largest retailers in the world.  During this process, the team realized that the process of developing AI-powered applications could be fully automated using best of breed open-source and home grown software systems. With the large number of high-quality open source algorithms readily made available in the open source by companies such as H2O.ai and Apache Spark, the ScoreData Engineering team led by product gurus Dr. Moidin Mohiuddin and Prasanta Behera created the ScoreFast™ platform. This platform allowed both business managers and data scientists to collaborate with each other to build highly robust, explainable and self-learning predictive models to solve hard problems in the enterprise. Scoredata’s platform is now able to deliver dynamically learning models on a software development and deployment system which boasts the lowest cost of ownership of any company in the world.

With the arrival of chief economist Dr. Ashok Bardhan to the team, the ScoreData team incorporated not only best-of-breed technologies, but also new econometric techniques and trade secrets into the predictive application development process. The resulting ScoreFast 2.0 platform has evolved into the world most powerful predictive applications development and deployment platform for customer engagement solutions which has consistently delivered profits while also being deployed cost-effectively.

Customer facing industries will see significant benefits not just in the time-to-market for predictive solutions, but also in the development of systems that learn on their own over time with little to no human intervention. These approaches not only help lower the total cost of ownership of machine-driven artificially intelligent systems, but also create an ethos of powerfully precise, bias-free decision-making and highly scalable and secure systems that optimize business goals for revenue, profit, and superior customer experiences.