Business users want to solve business problems. But existing data tools are focused around dashboards and statistical products are oriented around mathematical techniques. Dashboards are normally not enough, and technique-oriented tools are too advanced for most people. Either way, users are expected to know statistics and be coders. Businesses end up hiring data scientists just to use these tools.

We understand the disconnect between business problems and mathematical techniques and our machine-learning platform automates the bridge between business and math.

No Coding

Do not write a single line of code, or hire a data scientist. Just upload data, and set the business context by answering a few questions.

Bring Any Data
You Want

Accepts a wide variety of data sources and formats — CSV files to cloud sources like Pipedrive, Mixpanel etc. Let the platform connect to your preferred data source and generate the business context without any supervision.

Save Time from Data to Action

Automates 8-12 weeks of manual statistical model building and deployment work to 10-20 minutes. Use the platform from the first step of understanding your data, to the last mile of deployment using APIs.


Swarna Vallabhaneni

Swarna Vallabhaneni 

An engineer from IIT with an MBA from IIM Ahmedabad, Swarna is the key architect in conceptualising the product, building the server-side, and the data layer of Insight Jedi. He runs all technology aspects of Insight Jedi. Swarna started his career in a shipyard building ships, spend time in management consulting, and led teams in operations and sales at Dell. In his last corporate role, he was the Vice President for sales for India’s best looking online travel behemoth.

Dipayan Maiti

Dipayan Maiti 

A mathematician from IIT, Dipayan holds a PhD in Bayesian model selection from Virginia Tech. He is in charge of the algorithms that drive the models in Insight Jedi. Betweeen his MS and PhD, Dipayan was building risk models at JP Morgan Chase for three years. He also spent almost half of his time in graduate school building algorithms that create a story about an impending terrorist threat from thousands of news snippets, which can then be used by intelligence agencies.

Chandra Shekhar Jain

Chandrashekhar Jain 

An MBA from IIM Ahmedabad, Chandra began his career working for a niche Manufacturing Company which became a part of the Berkshire Hathaway Group. He handled everything from Operations, Building New Plant, Mergers, New Business Development in the fast growing company. He was a part of the Board of the Company when he ventured out on his own. He started a Business Analytics firm which provides solutions to the largest Retailers and CPG companies in the world. He is in charge of the Business Side at Insight Jedi. He is also one of the founder member of an NGO that works in the field of Hunger in India.

Ish Pandher

Ish Pandher 

Ish has a background in computer science and engineering with an MBA from UPenn. He worked at Bell and AT&T labs, early in his career, on optical networks and its applications. He moved on to designing and running trading systems, market data and execution algos at Nomura Securities, a big Japanese investment bank. Ish joined a top quant hedge fund in 2013 where he launched and built a successful crowd sourced model business and launched a deep dataset research initiative. He is now helping extend and adapt Insight Jedi Platform to meet the needs of financial service industry and runs the North American business development under the QuantSol brand.


Insight Jedi is a pure algorithms company, where all business problems are abstracted to a mathematical framework. This makes our product approach scalable to multiple problems across various domains. At Insight Jedi we want to solve a large class of business problems.

We are looking for exceptionally smart, motivated, self-learning, insanely curious and creative individuals in the field of computer-science, software-engineering, data visualisation, optimisation, economics, machine-learning and statistics, who can help us build and expand a robust machine learning platform.

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