Ankit Jha. From a small village in Jharkhand to enterprise AI.

Where it started

I was born in a small village and grew up in a small city in Jharkhand. By 14, bug bounty had become my hobby, cybersecurity was how I made sense of the internet, and I was already training police officers locally, speaking at tech events, and spending time around communities where both security research and the darker side of the ecosystem were visible up close.

Before AI was fashionable, I was trying to learn math, data science, and systems from first principles. In college, starting around 2016, I trained my first language model by myself to write rap lyrics. It failed badly, but it pushed me into deep learning. I paid for food with bug bounty, interned at messy early-stage companies, and eventually earned a government contract with the Election Commission of India, where we deployed computer vision systems used in real elections.

What came next

That work opened larger doors. I won hackathons, wrote widely, built a data science community, and kept solving hard modeling problems until I moved into enterprise roles across support AI, custom language models, mixture-of-experts systems, consulting for major pharma companies, and later work in Germany with Deutsche Telekom and at Delta Air Lines. Most of my projects have lived in high-stakes environments and carried million-dollar-plus impact.

On the side, I have always taught. I have trained thousands of students, worked with Univ.AI and faculty from institutions like Harvard and Stanford, and helped underprivileged students from unconventional backgrounds enter AI. Today I work on audio research at HBO Max, language preservation for Indian languages, and compact models that can reason, call tools, and simplify access to millions of government services. Enterprise General Intelligence is how I bring that same level of talent and execution to companies outside big tech, together with friends and collaborators from IITs, NITs, and serious engineering backgrounds.