- Current focus
- Avos AI: An operating system for trillions of AI agents.
- Based in
- San Francisco · Silicon Valley
- For investors
- Open to conversations on AI infrastructure & Avos AI.
I go after hard problems where complexity slows everything down and turn them into scalable systems.
The work began at seventeen. I founded an education-services company, grew it past 500 customers, and exited at twenty-one. In the same year I started a textile manufacturer in Bangladesh and scaled it from a single room to a $100K+ export business across five countries. Across these ventures I generated more than $500,000 in revenue and learned, first-hand, how to build operations that hold up under real demand.
I then pointed that operating discipline at research. Inside the company I built and led an applied R&D lab of seven, including two professors, that produced five peer-reviewed publications, 485+ citations, and a pending machine-learning patent in industrial prediction. The pattern has never changed: enter a hard domain, learn it from first principles, and turn the result into something people can use.
The foundation is formal as well as practical, an M.S. in Applied Data Science at 3.89 GPA and more than three years of audited, independent study in Stanford's AI ecosystem, spanning deep learning, transformers, ML systems, and self-improving agents.
Today, at Avos AI, I am building the context, memory, encryption, and control plane for a world where billions, and eventually trillions, of AI agents operate across software, business, and human systems.
“If the last era of software was built around apps and the cloud, the next will be built around autonomous agents, and those agents will need an operating layer they can trust.”