Stop building monolithic bots. The Agent Mesh provides the governance, orchestration, and connectivity layer that turns scattered AI experiments into a secure enterprise workforce.
Why separate the brain from the body? Focus and Safety.
"The Specialized Worker"
Holds the Cognitive Logic.
Possesses Domain Expertise.
Focuses purely on Reasoning & Solving.
"The Support Staff"
The Secretary: Connects calls and manages files.
The Guard: Ensures the agent doesn't delete evidence.
The Platform: Scalable infrastructure for 1000s of agents.
Service Mesh for AI: The Agent Mesh applies proven service mesh patterns—sidecar proxies, control planes, and observability—to autonomous AI workloads, enabling fine-grained traffic control and policy enforcement at the agent level.
Decoupled Governance: By separating cognitive logic from infrastructure concerns, organizations can independently scale, secure, and audit agent operations without modifying agent code or retraining models.
Enterprise Value: This architecture reduces integration complexity, provides unified audit trails for compliance, and enables heterogeneous agent deployments across cloud providers and on-premise infrastructure.
Governance isn't one step. It is a lifecycle that dictates how the Mesh is built.
"City Planning"
The strategic architectural roadmap before agents are built or bought. You map out the "Society of Agents," defining domains (e.g., "Finance Agent owns the General Ledger") and dependencies.
"Building Inspection"
Dependency mapping and refinement. This phase focuses on refactoring monolithic logic into sub-agents, defining clear skill boundaries, and verifying catalog registration.
"Security Guard"
Dynamic interception. As the agent runs, the Mesh monitors inputs and outputs in real-time.
How do we enforce the governance lifecycle? We need five critical pillars that handle discovery, workflow, connectivity, authorization, and observability.
This supports Plan-Time Governance. By registering agents here, we ensure discovery and prevent overlap.
The execution engine. It ensures the strategic plan (Phase 1) is actually followed during runtime.
The control point for traffic. This is where the rubber meets the road for security policies.
Policy-Based Access Control (PBAC) for dynamic, context-aware authorization decisions.
Continuous monitoring, tracing, and learning from agent behavior across the mesh.
Prevent vendor lock-in by separating the Worker from the Office.
Universal protocol for connecting data sources (Google Drive, Slack) so you swap backends without rewriting agents.
Defines a universal API spec for communicating with an agent (tasking, listing steps, getting artifacts).
Allows two autonomous agents to perform a 'handshake' and negotiate tasks without a central orchestrator.
A manifest file (like robots.txt) where agents document their own capabilities for other robots to read.
Don't confuse the tool you use to build the agent with the infrastructure that runs it.
"The Car Factory"
This is where you write code, optimize prompts, and run evaluations. It's about creation and iteration.
"The Highway System"
This is the production environment where the agent lives. It handles traffic, security, and connectivity to the enterprise.
Prevent Agent Sprawl. Centralize policy enforcement so you don't have thousands of rogue agents hitting APIs without oversight.
Write Once, Run Everywhere. Build a "Salesforce Tool" once and let 50 different agents across Finance, Sales, and Support reuse it.
Forensic Traceability. When a chain of autonomous agents fails, the Mesh provides the "black box" recording to pinpoint exactly which agent made the bad decision.