# The Multi-Agent Negotiation — Mnemom Case Study

[Enterprise](/enterprise)

Case Study

# The Multi-Agent Negotiation

Trust-gated multi-agent coordination

## The Challenge

Four AI agents from different organizations need to collaborate on a complex task via the A2A (Agent-to-Agent) protocol. The orchestrator has no way to assess which agents are trustworthy and which might introduce risk to the collaboration.

## The Solution

The orchestrator queries Mnemom's Trust Directory before admitting agents to the negotiation. ReputationGate — a middleware layer — automatically rejects agents below a configurable Trust Rating threshold. Coherence analysis runs continuously during the collaboration, flagging any behavioral drift from declared alignment cards.

## The Outcome

An untrusted agent (Trust Rating 340, CCC-rated) is automatically rejected from the collaboration. The remaining three agents complete the task with continuous integrity monitoring. Every interaction produces a verifiable audit trail.

## Key Details

-   ReputationGate middleware for A2A protocol
-   Configurable Trust Rating admission thresholds
-   Continuous coherence monitoring during collaboration
-   Per-interaction integrity checkpoints and certificates

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