Generative AI
Put language models to work on problems that pay back.
Most generative AI projects stall somewhere between the demo and production. We work on the unglamorous parts that decide whether a system survives contact with real users: grounding answers in your own data, measuring quality before launch rather than after, controlling cost per request, and giving your team a way to tell whether a change made things better or worse.
- Retrieval systems over internal documents and records
- Assistants and agents wired into the systems you already run
- Evaluation harnesses and regression suites for model output
- Cost, latency and guardrail design for production workloads