AI that does real work in your operations.

Most AI projects stall between the demo and daily use. We start by looking at the work itself: which steps are slow, which ones a model can do reliably, and which ones still need a person. You get a written assessment with the expected accuracy, the running cost and the risks, and we tell you when a simpler approach is the better answer.

Then we build. Our engineers have shipped systems that read insurance documents, lab reports and identity cards and turn them into structured fields; agents that log in to licensing boards and payer portals, check what they find, and repair themselves when a portal changes, with a person approving every fix; a voice scribe and phone-camera wound measurement used at the point of care; and question answering over a curated medical knowledge base. The work uses OpenAI, Anthropic and open models, chosen per task.

Every system ships with an evaluation set, so accuracy is measured rather than assumed, and with review steps for cases the model is unsure about. After launch we run it like any other production system: we monitor accuracy, cost and drift, and we keep it inside your security and compliance boundary. AI work runs on the same cloud, DevOps and security practices as everything else we build.