I build production AI systems — not prototypes. From LLM architecture to agentic workflows, I help companies ship AI that stays shipped.
Most AI projects don't fail because the tech doesn't work. They fail because nobody connected it to the business.
AI projects stall between POC and production. Models work in notebooks but never reach the people who need them.
The POC looked great on clean data. Real documents, edge cases, production volume — that's where it fell apart.
Every API call uses the most expensive model. No caching. No batching. No model routing.
Most AI consultants hand you a strategy deck. I hand you a working system.
Autonomous agents with human-in-the-loop guardrails. Natural language interfaces that drive real adoption — not just demos.
70% adoption boostMulti-model extraction pipelines processing 1M+ documents at 91% straight-through rates. The full stack.
production volumePrompt caching, model routing, and batch processing. Same quality, half the spend. Typical payback: week one.
50%+ savingsNo handoffs, no translation loss. Stakeholder interviews through production deployment — independently.
full stackNatural language to automated workflow in 30 seconds
Watch 1M+ docs flow through multi-model extraction
How prompt caching cut API costs by 50%+
Via agentic workflow design that solved the adoption bottleneck, not just the capability gap.
Through prompt caching, model routing, and batch processing — same quality, half the spend.
1M+ documents processed with minimal human intervention across financial, legal, and healthcare domains.
Repeatable methodologies refined across 12+ enterprise engagements.
Stakeholder interviews, feasibility scoring, and a phased roadmap. Turn "we want AI" into an action plan with clear ROI.
Autonomous AI agents that remove human bottlenecks. NL interfaces, tool orchestration, human-in-the-loop safeguards.
Prompt caching, model tiering, token optimization, and provider arbitrage. Typical payback: week one. 50%+ savings.
End-to-end extraction: ingestion, OCR, layout analysis, multi-model consensus, validation, and monitoring.
He didn't just build the model — he redesigned how our team interacts with the output. That's what moved the needle on adoption.
Most consultants need hand-holding. Rishabh took our vague brief, mapped the architecture in a week, and had a working system in four.
We were spending 3x what we needed on LLM costs. He cut our bill in half in the first week — and output quality actually improved.
* representative of real engagement outcomes — named testimonials coming soon
Let's talk about what's broken, what's possible, and what ships first.
Book a Discovery Call →30 min. no pitch deck. just a real conversation. ☕