Infrastructure between a model and the systems it has to use.

Layers

1. 01

   Input layer

   Accept structured and unstructured inputs, including text, events, and visual information.

2. 02

   Intent layer

   Interpret the goal an agent or user is trying to accomplish.

3. 03

   Connectivity layer

   Communicate with external APIs, data providers, and software platforms.

4. 04

   Entity layer

   Identify and reconcile companies, people, securities, jobs, products, collectibles, and other entities across systems.

5. 05

   Intelligence layer

   Structure, rank, match, compare, and contextualize information.

6. 06

   Evidence layer

   Preserve provenance so outputs stay connected to underlying source material.

7. 07

   Action layer

   Allow approved agent workflows to perform actions through external systems.

8. 08

   Governance layer

   Manage permissions, authentication, logging, and operational boundaries.

9. 09

   Outcome layer

   Measure what happened after an agent recommendation or action.

More than one ecosystem

AgentStructure creates infrastructure and connectors for AI agents across multiple ecosystems. Inclusion below is a design target. It is not a partnership, a listing, or a certification.

• Agent platforms

  Hosts where agents plan, call tools, and return work to a user.

• Model providers

  The infrastructure is not tied to a single model vendor.

• MCP ecosystem

  Tool definitions that agents can call through MCP-compatible hosts.

• Enterprise agents

  Permissioned workflows inside company software boundaries.

• Developer APIs

  Direct interfaces for teams building their own agents.

• AI marketplaces

  Distribution through agent and app marketplaces. Muse is one possible ecosystem, not the architecture.

• Commerce platforms

  Listing, catalog, and transaction workflows an agent may assist.

• Data providers

  Authorized datasets exposed through controlled agent interfaces.