A model can propose a purchase. Only your organisation can authorise one. BuildAI qualifies each release, checks every consequential action against live policy, brings in the right person when it matters, and keeps evidence you can defend.
BuildAI sits between AI models and the systems they act on. It qualifies a release against versioned evaluations, checks every consequential action against live policy, routes high-risk actions to the right human, and records evidence that separates what was proposed from what really happened.
No. Models provide the intelligence; BuildAI decides what that intelligence may do. You connect your own model providers, and a model's output is always treated as a proposal, never as permission.
Create a workspace and connect your model providers to start building. For a governed rollout on your own workflow, request an enterprise evaluation and we will scope it with you: the workflow, the risk it carries, who approves what, and the evidence your reviewers need.
An approval binds to the exact action: the tool, target and arguments. It expires, it can be used once, and high-risk requests need someone other than the requester. Changing the amount or the recipient invalidates it.
Model judges grade cases against a rubric and are calibrated against independent human labels, with agreement, kappa and sample size reported. A model label can never override a deterministic safety failure, and it never qualifies a release on its own.
Operators open an incident, link the affected runs with an evidence snapshot, and act from there: stop an execution, cancel a run, disable a deployment or suspend a member. Every step lands on a tamper-evident timeline. Stopping blocks new actions; it never pretends to undo what already happened.