AI that knows your business.
Retrieval, agents and copilots that read from governed enterprise data, with evaluation, guardrails and cost control built in.
What we build
Retrieval applications
Answers grounded in your documents and data, with sources people can check.
Agents and automation
Multi-step workflows that act inside your systems, with a human where it matters.
Document intelligence
Contracts, claims and forms turned into structured, searchable data.
Evaluation and guardrails
Test sets, monitoring and limits, so quality and cost stay where you set them.
How it's architected
The same platform your analytics trusts.
- Databricks
- PostgreSQL
Documents and records chunked, embedded and kept in sync.
- Vector databases
The right model for each task, swappable as better ones arrive.
- LLM APIs (Claude, OpenAI, open models)
Retrieval, tools and agents composed into reliable flows.
- LangChain / LangGraph
- Python / FastAPI
Every release measured against your own test cases.
- MLflow
Copilots, search and assistants inside the tools people use.
- React / Next.js
- TypeScript / Node.js
Faster answers, fewer manual steps, decisions people can trace.
Typical engagements
Proof of value
One use case, real data, measured against a baseline in weeks.
Production rollout
A pilot hardened with evaluation, security and cost controls.
AI platform
Shared retrieval, model access and guardrails for every team.
Technologies we work with
- Python / FastAPI
- LangChain / LangGraph
- Vector databases
- LLM APIs (Claude, OpenAI, open models)
- MLflow
Where we apply it
Have a complex problem?Let's engineer the solution.
Tell us what you're trying to build, improve, automate or understand. We'll help you find the technology path forward.