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Govern the handoffs your orchestration framework misses

LangGraph, AutoGen, CrewAI give you orchestration. They don't give you governance.

You're orchestrating multiple AI agents. Every handoff is a potential attack surface. QuilrAI watches every agent-to-agent call, every tool invocation, every data access, and enforces scope automatically.

Without Governance

What goes wrong at runtime

Agent frameworks handle orchestration logic. They were never designed to enforce security boundaries between agents.

Scope creep across agents

Agent A asks Agent B for help. Agent B calls 10 tools. None of those tools were in your original policy. You find out 3 weeks later.

Cross-agent data leakage

One agent handles PII. Another handles external APIs. Without governance, PII travels to places it was never supposed to reach.

Privilege escalation

An orchestrator agent inherits permissions from every sub-agent it spawns. Before long, it has access to everything.

How QuilrAI Governs It

Scope isolation. Data tracking. Least privilege.

Guardian policies attach to individual agents, not the system as a whole. One compromised agent can't take down the rest.

Scope isolation per agent

Each agent in your network gets its own Guardian policy. Agent A can only call what Agent A is permitted to call, regardless of who asked.

Data flow tracking

QuilrAI tracks data sensitivity labels across agent handoffs. PII that enters Agent A can't exit through Agent B without redaction.

Least-privilege spawning

When one agent spawns another, the child gets a subset of the parent's permissions, never more.

Guardian Setup

Governance decisions, not just configuration

Guardian walks you through the critical choices for your agent network, and enforces them at runtime.

guardian setup · your multi-agent system
clarify
  • Allow cross-agent communication?

    Agents: researcher → writer → reviewer

    Approved
  • Allow agent spawning?

    Scoped to: child gets subset of parent permissions

    Approved
  • Data sensitivity: PII [likely], Internal IP [likely]

    Redact on cross-agent transfer
Supported Frameworks

Works with the orchestration stack you already use

QuilrAI integrates at the agent boundary, no changes to your orchestration framework required.

LangGraphAutoGenCrewAILlamaIndex WorkflowsHaystackCustom PythonAny MCP-based system
Deployment

Three steps to a governed agent network

From registration to runtime protection, without rewriting your orchestration layer.

01

Register your agent network

Describe each agent's role and purpose. QuilrAI understands the graph before it runs.

02

Guardian maps the graph

Scope, data flows, and permissions are set per agent, not per system.

03

Ship governed

Every handoff monitored, every violation blocked. Zero changes to your orchestration code.

Common Questions

Multi-agent security, answered

What is privilege escalation in multi-agent AI systems?

Privilege escalation in multi-agent systems occurs when a sub-agent is granted permissions that exceed what the orchestrating agent was authorized to delegate. For example, a researcher agent delegating database write access to a writer agent when the researcher itself only had read access. QuilrAI enforces permission boundaries at every delegation hop.

How does QuilrAI govern agent-to-agent delegation?

QuilrAI assigns a Guardian Agent to each AI agent in a multi-agent system. When Agent A delegates a task to Agent B, QuilrAI intercepts the handoff, verifies that the delegated permissions don't exceed Agent A's own scope, and blocks unauthorized capability expansion before it reaches Agent B.

Can prompt injection travel through multi-agent chains?

Yes, prompt injection payloads embedded in documents, web pages, or tool outputs can propagate through multi-agent chains as each agent passes context to the next. QuilrAI scans all inter-agent messages for injection patterns and sanitizes payloads before they reach downstream agents.


Every handoff monitored. Every violation blocked.

Ready to govern your agent network? See how Guardian handles agent-to-agent communication, scope isolation, and data flow tracking in an interactive walkthrough.