Agents, copilots, and RAG-backed apps — with evals, so regressions show up in CI instead of in Slack screenshots.
Not a chatbot glued onto your homepage. Retrieval pipelines, tool-using agents, structured extraction, and the product UI that makes the model useful. We pick models for the job — OpenAI, Anthropic, or open weights — and keep you from locking into a demo that can't scale.
If we can't measure whether the model is getting better, we don't ship the feature. Golden sets, regression suites, and human review loops are part of the architecture, not a slide in the retro.
Stuffing the entire docs site into a context window and calling it RAG. We will tell you when a rules engine or a search index is the better product — cheaper, faster, and easier to trust.
Also useful
Talk to the engineer who would actually write the code. Thirty minutes, no deck.
