AI Engineering

I build production-grade AI systems — from conversational chatbots with semantic search to automated data extraction pipelines. My AI engineering goes beyond prototypes: I deliver fine-tuned models, RAG architectures, and intelligent features that integrate seamlessly into your existing stack.

The highest-impact AI work is rarely a chatbot. It's operational systems that extract data, clean messy files, connect to your tools, and stay reliable in production.

What this looks like

01

Documents

Receipts, forms, reports, contracts. Extract structured data — or fill forms from uploads.

02

Messy files → usable data

Business data lives in PDFs, decks, and reports. Clean and structure it so AI can search and act on it.

03

Connect AI to your tools

Update a database, check inventory, send a report, start a workflow. AI that does work — not just talk.

04

Make it reliable

Demos are easy. Production needs accuracy and consistency. Eval, improve, ship systems your team trusts daily.

GPTClaudeLangChainVector DBsRAGFine-tuning

Related Insights

The AI Engineering Platform Every Company Rebuilds→Where AI Actually Creates Business Value→Why AI Pilots Die Between Demo and Production→From Documents to Structured Data: Anatomy of a Production Pipeline→Human-in-the-Loop Is a Feature, Not a Weakness→

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