An LLM developer who takes prototypes to production.

• RAG and semantic search with hybrid retrieval and citations;
• multi-step agents with tools, memory and guardrails;
• structured extraction from text and documents into JSON, databases and business systems;
• evaluation suites and automated regressions;
• cost and latency optimization: the right model per task, caching, fewer tokens.

1. 01Discovery. Before any code: interviews, a look at the data you already have, technical and business constraints on the table.
2. 02Architecture. Data schema, component boundaries and failure points decided on paper, when changing them costs an hour and not a month.
3. 03Build. Short iterations with working demos instead of one delivery at the end. AI speeds things up where it makes sense; it never replaces review and testing.
4. 04Handoff & scaling. Documentation, runbooks and a system your team can run without depending on me. No lock-in.

Every project is priced after a scoping call: the same word, "chatbot" or "agent", can mean a two-week prototype or a system in production for thousands of users. What moves the price:

• fixed-scope project or time-boxed team augmentation;
• maturity of the existing code and data;
• quality, security and logging requirements;
• expected users and volumes.

The first call is free and ends with a clear answer: whether the project makes sense, roughly how big it is, and what to do first.