Skip to content

AI Product Engineering

We build AI features that survive contact with real customers. That means production-grade models such as Claude and OpenAI, connected to your own data, with retrieval, guardrails, evaluation, and cost controls engineered in — not a demo prompt wrapped in a chat box.

AI assistant, document intelligence and workflow automation architecture
What you get

Built to hold up in production

AI assistants and chatbots

Support and sales assistants that answer from your own content and hand over to a human at the right moment.

Document intelligence

Ask questions across contracts, PDFs, and knowledge bases with citations shown for every answer.

Workflow automation

Classify, extract, route, and draft — taking the repetitive work out of support, admin, and operations.

AI inside your existing product

Smart search, recommendations, or generation added to the app you already run, without a rewrite.

What's included

  • Use-case feasibility and cost review
  • Model selection and integration architecture
  • Secure retrieval over your own data
  • Evaluation suite and accuracy benchmarking
  • Guardrails, rate limits and monitoring
  • Production deployment plus ongoing tuning

Technologies we use

Claude APIOpenAI APIPythonFastAPILangChainVector databasespgvectorNext.jsNode.jsAWS Bedrock

Not sure which of these fits?

Stack choices are trade-offs between cost, speed, and who you will be able to hire in two years. Tell us your constraints and we will make the case for a specific option in writing — no obligation.

Ask for a recommendation
FAQ

AI Product Engineering — common questions

The questions clients actually ask before signing off on this work.

Production-ready hosted models — principally Claude and OpenAI — chosen per use case for accuracy, latency, and cost. This ships a reliable feature far faster and cheaper than training your own, and the architecture lets you switch models later as the field moves.

Usually not. Most business AI features retrieve from your existing documents and systems at the moment of the question, so the content you already have is normally enough to start.

Yes. We use business API tiers that do not train on your data, keep sensitive records inside your own infrastructure where required, and agree the data-handling terms in writing before we begin.

By grounding answers in retrieved sources, showing citations, constraining the model with system rules and structured outputs, and running an evaluation set before every release. Where the answer is uncertain, the system is designed to say so or escalate to a human.

Ongoing cost tracks usage, since models bill per request. We estimate it before we build, design for efficient token use and caching, and add monitoring plus hard limits so the bill stays predictable.

Ready to start your ai product engineering project?

Send us the requirements — or just the problem — and we will come back with a fixed-price quote, usually within one business day.

  • Reply within 1 business day
  • NDA on request
  • You own the IP
  • No sales sequence