Governance for the multi-agent era.
When AI agents communicate, delegate, and collaborate autonomously, governance ensures every interaction is compliant, auditable, and within policy boundaries.
When AI agents communicate, delegate, and collaborate autonomously, governance ensures every interaction is compliant, auditable, and within policy boundaries.
Traditional AI oversight assumes a single model responding to a single user. In agentic architectures, AI systems hand off tasks, share context, and escalate decisions across a network -- creating blind spots that existing frameworks cannot address.
When Agent A delegates a subtask to Agent B, who delegates further to Agent C, accountability fragments. Each handoff is an opportunity for policy drift, data leakage, or unauthorized action.
Agents share reasoning chains, intermediate results, and sensitive data as they collaborate. Without governance, PII and confidential information can flow to agents that should never see it.
An agent authorized for read-only research can request a peer agent to take write actions on its behalf -- effectively escalating its own privileges through the multi-agent mesh.
When decisions span multiple agents across different services, reconstructing the full chain-of-custody for a single outcome becomes nearly impossible without a unified governance layer.
KoraSafe™ sits between every agent-to-agent interaction, enforcing policies, logging exchanges, and ensuring compliance without slowing down your multi-agent workflows.
Every capability your multi-agent system needs to operate safely, compliantly, and with full observability across every agent interaction.
Every agent-to-agent call is logged with full context: who initiated, what was requested, what data was exchanged, and what actions resulted. Tamper-evident audit trails for every handoff.
Define granular rules for what agents can delegate, which peers they can communicate with, and what data types are permitted in each exchange. Policies evaluated in real time at every interaction point.
Prevent unauthorized privilege escalation across the agent mesh. If an agent attempts to request actions beyond its authorization scope through a peer, KoraSafe™ blocks and flags the attempt.
Track data lineage as information flows across agents. Know exactly which agents touched a piece of data, what transformations occurred, and whether any policy boundaries were crossed along the way.
Before any agent-to-agent interaction, KoraSafe™ validates agent identity, confirms capability authorization, and verifies the requesting agent is permitted to invoke the target agent's functions.
Unified compliance posture across your entire agent fleet. Aggregate cross-agent interaction data into regulatory-ready reports covering EU AI Act, NIST AI RMF, and internal governance frameworks.
The capability set decomposes into named guardians. Each one fires on a specific failure mode that traditional single-agent governance does not catch.
Reads the delegating agent's registered scope and compares it against the delegation message's implied scope. Blocks when the delegated scope is a superset of what the delegator can do. Catches privilege escalation through the agent mesh.
Pattern library against prompt-injection attempts that ride on inter-agent messages and retrieved documents. Covers OWASP LLM02 attack variants and the agent-system-override patterns that emerge when one agent's output becomes another's input.
HMAC token system plus a behavioral fingerprint per agent. Validates that the agent on the wire is the agent it claims to be. The fingerprint accumulates over time so impersonation detection sharpens with every additional exchange.
Computes cosine drift between the task as the orchestrator stated it and the task as it appears at each downstream hop. Flags when context corruption crosses the configured threshold so a 100-agent chain does not produce silent garbage at hop five.