We build the boring 90% that makes AI work.
What we build
Two weeks to learn where AI pays off for you, and where it does not. Fixed scope, agreed in writing.
More on AI AuditAgents that take real actions in your tools, with a person approving the steps where the stakes are high.
More on AI AgentsAnswers from your own documents that cite the page they came from, measured against a golden set.
More on RAG SystemsCopilots, search, summaries and drafting, built into your own product.
More on GenAI DevelopmentBackends, integrations and internal tools: the plumbing that keeps AI running.
More on Software DevelopmentWebsites and web apps that are fast, accessible and easy for your team to update.
More on Web DevelopmentResearch, flows and design systems for interfaces people trust, including AI ones.
More on UI/UX DesignThe model is about 10% of an AI system that works. We build the other 90%: data, retrieval, evals, integrations, guardrails, serving, monitoring and interface.
How we work
We map the problem, the data and the risks before anyone writes code. Usually the AI Audit.
[Senior engineers] work in your repositories and your cloud, and show working software every week.
A production rollout with evals, monitoring and a runbook your team can operate.
We watch accuracy, speed and drift and keep improving what matters, or hand over cleanly.