From research paper to production to revenue.
AI is all you need.
The work
Closing the distance between a demo and something a customer will actually run.
I build AI products and work out who will pay for them. I started as an engineer at Samsung R&D, moved into strategy consulting at Accenture, founded an AI company that was acqui-hired in 2024, then joined Nurix AI as a founding member. Today I am a Research Project Manager at Deccan AI.
Those jobs taught me the same lesson from different angles. The hard part of enterprise AI is rarely the model. It is the distance between something that works in a demo and something that survives a real customer, a real budget, and a real security review.
Closing that distance is the work I care about, and it is what I write about here. Most essays take one research paper, rebuild its central idea, and ask a single question: would this survive production?
Ship the PaperEvaluation
LatestA new paper lets an AI judge keep only the verdicts it is sure of, with a stated cap on how many can be wrong. I rebuilt it on a laptop to find where that cap stops holding.
Generative AIModels
I fine-tuned the small model that reads my stock-exchange filings, and named it Argus. Claude refused to teach it, so an open model did, and Claude graded the exam.
Generative AIModels
TypeSafe's Jev answers with a probability instead of a paragraph. I wanted to know when you can let that probability make the call, so I built a small test.
Ship the PaperEfficiency & Serving
FinCacheServe lets a financial assistant reuse finished answers until a filing changes. I rebuilt its reuse check to see whether an up-to-date answer is also the right one.
Ship the Paper
01A calibrated LLM judge, rebuilt on a laptop. Its cap on wrong verdicts held where it was calibrated, and quietly broke on a kind of question it had never seen.
Generative AI
02One tiny model trained three ways on a refund desk, changing only the reward. Only a scored confidence was safe to act on, until the queue spoke more Portuguese.
Ship the Paper
03A replay of FinCacheServe's reuse check over amended filings. It never served a stale answer, but it did serve fresh answers to sibling questions, and its own metric called them safe.
If you are working on enterprise AI and stuck somewhere between the demo and the contract, that is the conversation I enjoy most.