One AI partner.
Every industry.

Industry expertise is an overused claim, so here is what we mean by it. Every sector has one thing that decides how an AI system must be built long before anyone chooses a model, and it is almost never the technology. In pharmaceuticals it is GxP validation, which means a change needs documented evidence before it reaches production. In hiring it is that a rejected candidate can ask why, so the decision has to be explainable and bias-tested. On a factory floor it is that the network is unreliable and the decision has to happen locally in milliseconds.

Those constraints are not obstacles we work around at the end. They are the first input to the architecture, because a system that ignores them gets built twice. A defect detector that assumes connectivity is a prototype; a claims agent without an audit trail is a liability; a clinical copilot that cannot cite its source will not survive its first review meeting.

Each page below starts from that constraint, then covers the systems of record we integrate against, the regulations in scope, and the workloads worth automating first in that sector.