Point-of-call enforcement
Policy applied at the request, not after. Blocked prompts, redacted prompts, allowed prompts — logged with rationale.
04/products/ai-governance · ProductVol. I · Issue 01 · Q3 2026
PLATFORM · P03
BUILT
AI Governance
Every AI call in your enterprise intercepted, policy enforced, and logged.
A control you cannot evidence is not a control — it is an intention. AI Governance sits at the point of every LLM call and every agent action, enforces the policy, prevents the leak, and logs the trace.
01 · The problem
What ai governance is for.
- Employees using AI you have no visibility of
- Sensitive data leaving the perimeter through prompts
- No log a regulator would accept as evidence
- AI policy that lives in a document nobody reads
- Vendor LLMs training on your data by default
- A board question you cannot answer: what did our AI do last quarter?
02 · What is in it
The capability.
Local ML DLP
Data loss prevention against your own model, on your own hardware. No external inspection of your prompts.
Full audit trace
Every LLM call, every agent action, every model response. Structured for board committee and regulator query.
Identity-aware
Integrated with your enterprise identity. Right person, right model, right data — enforced.
03 · The distinctive mechanic
The evidence layer.
Most AI governance tools produce dashboards. AI Governance produces evidence — the specific query, the specific model, the specific enforcement decision, the specific person, at a specific time. Enough for a regulator to accept, and small enough to fit in a board pack.
04 · Who it is for
Regulated enterprises with existing AI usage that cannot see it clearly. Chief risk officers, chief data officers, chief information security officers. Board risk committees who now have to explain AI to the audit committee.
Run ai governance in your business.