AI agent governance — a control plane that scales from dozens to hundreds of agents

Once you run more than a handful of AI agents in production, governance debt explodes. Agents proliferate across teams, reuse the same data products and tools, and nobody knows which agent made which decision. AI-Koutsi provides the operational control plane: registry, roles, tool permissions, guardrails, monitoring, HITL and full audit trail.

Agent registry as the source of truth

Every agent is registered with its role, owner, data products, tool permissions, model tier and EU AI Act risk class. Tool calls and decisions are logged with full lineage. Auditors see the same view as the CDO.

Guardrails wired to the canonical control library

Guardrails attach automatically based on risk tier and industry. Adding a new agent does not require re-deriving policies — the canonical library covers EU AI Act, NIST AI RMF and ISO 42001.

Model tiers and cost discipline

Reasoning, Standard and Light model tiers are matched to task criticality. The platform reports per-agent cost and quality, so the right tier can be chosen deliberately — typical LLM cost savings are 30–50%.

Frequently asked questions

How is this different from LangChain or AutoGen?
LangChain and AutoGen are agent-building frameworks. AI-Koutsi is the governance layer above them: it answers who owns each agent, which data products it uses, what risk tier applies, and how to audit it — across all frameworks you happen to use.
Does AI agent governance cover the EU AI Act?
Yes. Every agent is classified against EU AI Act risk tiers and tied to the required controls and monitoring rules. DPIA and conformity assessment artifacts are generated from the portfolio.