AI Integration.
AI features that ship. Not demos.
LLM features, agents and automation built into your product. From retrieval to tool calling. Built by someone who works AI-native every day.
Automation that does real work. With a human where it counts.
Edge cases route to people. That is the design, not a failure.
Six pieces. Assembled for your product.
Retrieval
Answers grounded in your data, with sources. Not model guesswork.
Agents & tools
LLMs that call your systems. Read, decide, act, report back.
Structured output
Validated JSON your backend can trust. Retries on mismatch.
Evals
Quality measured on real cases. Before launch and on every change.
Streaming UX
Responses that feel instant. Loading states designed, not ignored.
Cost control
Model tiers, caching, budgets per feature. No surprise token bill.
Deliverables. Shipped, not sketched.
- ✓LLM features inside your product. Chat, search, extraction, summaries.
- ✓Retrieval pipelines over your own data. Grounded answers, cited sources.
- ✓Agent workflows with tool calling. Automation that does real work.
- ✓Provider-agnostic setup. Anthropic, OpenAI or local models behind one interface.
- ✓Evals and guardrails. You know how it behaves before your users do.
What I do differently. AI-native, product first.
- 01I work AI-native every day. This is my own workflow, not a trend I read about.
- 02Product first. The model serves the feature, never the other way around.
- 03Cost and latency budgets per feature. The token bill stays predictable.
- 04No demo-ware. Every integration ships with error states and fallbacks.
What I guarantee. In writing.
- 01Working features in production, not a slide deck.
- 02Measured quality. Evals run before and after every change.
- 03Full source, prompts and pipelines. You own everything.
- 0430 days of free fixes after launch.
Why me. Judgment over hype.
- 01Senior engineer, ten years shipping. AI-augmented on every step.
- 02I run LLMs in my own products. I know where they break.
- 03One person from data to UX. No handoff between an AI team and devs.
- 04You get engineering judgment, not hype.
Also available embedded. Your team, this discipline.
Not every project needs the full chain. If you run your own team, I join it in exactly this discipline. As a freelancer, inside your workflow.
- 01AI engineer in your product team. LLM features, agents, pipelines.
- 02Anthropic and OpenAI APIs, retrieval, evals, function calling.
- 03Brings an AI-native workflow into your team. Your devs level up too.
- 04Part-time or full focus. Weekly availability agreed up front.