AI governance refers to how model risks, outputs, and processes are controlled, reviewed, and documented. It’s essential for compliance, transparency, and production trust.
LLMs require prompt traceability, output filters, and hallucination checks — which we layer on top of classical MLOps pipelines.
Yes. We use CI/CD hooks, policy-as-code, and streamlined reviewer flows — ensuring delivery velocity with no compliance tradeoff.
Lack of runtime enforcement. Most orgs rely on documentation and manual checks instead of embedding controls into the actual delivery flow.
Yes — we’ve built pipelines with end-to-end lineage, policy enforcement, and audit support across regulated healthcare and finance teams.
Book a quick audit of one model or pipeline — and we’ll map gaps, propose controls, and scope an implementation path.
