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. Immutable 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.
Four specialized agents scan code, audit dependencies, generate fixes, and monitor runtime behavior across every surface.
Scans agent source code for governance violations: missing human-in-the-loop gates, hardcoded secrets, PII exposure, and non-compliant data handling. Maps every finding to specific regulatory controls across EU AI Act, GDPR, and HIPAA.
Scans npm and pip package manifests for known CVEs, license compliance issues, and supply chain risks. Cross-references against the NVD and flags transitive dependencies that introduce governance exposure.
Generates targeted code patches for governance findings. Produces drop-in fixes with regulatory context explaining why the change is required and which controls it satisfies. Available via the /fix command in the KoraSafe agent bar.
Processes real-time observations from the browser extension: LLM API calls, shadow AI usage, and PII in chat inputs. Correlates runtime behavior against org policies and triggers alerts when violations are detected.