The governance layer for AI agents.|
Audit trails and policy enforcement for agents in production.
The autonomous trust gap.
Gartner predicts that by 2028, 15% of day-to-day work decisions will be made autonomously by agentic AI. LangGraph and CrewAI can orchestrate these agents, but no standard layer governs what they do once deployed. Production agents need audit logs, policy gates, and human approval before they delete emails or execute trades.
Where teams deploy it
Financial Agent Governance
Cap spending per agent and require human approval before any trade executes. Every transaction gets a tamper-proof audit entry.
Customer Support QA
Sensitive escalations pause for manual review. Low-risk actions like password resets flow through automatically.
Internal Data Security
Row-level policies block RAG agents from surfacing PII in tool responses, whether they run on GPT-4, Claude, or Gemini.
Where Nyantrace fits
LangGraph orchestrates agents. LangSmith traces them. Nyantrace governs what they're allowed to do.
| Capability | Nyantrace | Guardrails AI | LangSmith | Platform-Native |
|---|---|---|---|---|
| Action governance (tool calls) | ✓ | — | — | ✓ |
| Tamper-proof audit (hash chain) | ✓ | — | — | — |
| Multi-agent coordination health | ✓ | — | — | Partial |
| Human-in-the-loop approvals | ✓ | — | — | ✓ |
| Kill switches & incident response | ✓ | — | — | ✓ |
| Framework-agnostic | ✓ | ✓ | Partial | — |
| Vendor-neutral | ✓ | ✓ | Partial | — |
| Development tracing | ✓ | — | ✓ | ✓ |
| Content safety (LLM outputs) | — | ✓ | — | ✓ |
See governance
in action
Book a 30-minute demo. We'll deploy governance on your agents and show the audit trail recording live.