AI Integration for Existing Products
You have a product and a stack that works. You don't need it rebuilt — you need AI added to it cleanly: a copilot, retrieval over your own documents, an agent that takes real actions. The hard part isn't calling an API; it's making it reliable, safe, and cheap enough to run at scale.
What you get
Retrieval over your data (RAG)
The model answers from your documents, tickets, or knowledge base — accurately, with citations, and without hallucinating your business away.
Agents & tool-use
AI that does things in your systems — with the tool definitions, permissions, and approval gates to keep it safe.
Cost & reliability control
Caching, fallbacks, rate limits, and evaluation so quality holds and the bill doesn't surprise you.
How I work
Integration means fitting your existing stack, not replacing it. The work slots into your codebase and ships behind the reliability and monitoring a production feature needs.
FAQ
Which AI providers do you work with?
Anthropic (Claude), OpenAI, and open models — chosen to fit your latency, cost, privacy, and quality needs, and swappable so you're not locked in.
Can the AI answer from our own data?
Yes — a retrieval pipeline grounds the model in your documents so answers are accurate and traceable rather than made up.
Will this fit our existing codebase?
Yes. Integration is designed around your current stack and shipped as maintainable code your team can own.