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The Siesta AI reference architecture separates user-facing application services, API and workflow services, retrieval services, tool integrations, managed data services, AI services, security stores, and operations telemetry.

Sanitized Azure reference architecture showing edge protection, application services, private networking, data, AI, identity, secrets, messaging, storage, and monitoring

The diagram is intentionally logical. It does not expose customer resource names, private addresses, quantities, sizing, or environment-specific topology.

Logical Flow​

Users and clients
       |
Ingress, TLS, WAF, and identity
       |
Frontend and API services
       |--------------------------|
Agent and workflow runtime        Tool and connector services
       |                          |
Retrieval API and workers         Approved external systems
       |
Search, storage, and databases
       |
Approved model deployments

Cross-cutting: Key Vault, managed identity, private networking,
monitoring, audit evidence, backup, and policy controls

Service Boundaries​

  • Frontend presents authenticated and approved public interfaces.
  • Platform API handles platform logic, agent configuration, workflows, and authorization.
  • Retrieval services ingest, chunk, index, and retrieve approved knowledge.
  • Tool services isolate integrations and external function execution.
  • Background and function workloads handle asynchronous processing and scheduled work.
  • Managed data services store application records, files, indexes, and job state.
  • Model deployments provide chat, reasoning, embedding, audio, or other approved inference.
  • Operations services collect logs, metrics, traces, health, and security signals.

Customer deployments can change naming, region, sizing, network integration, and service ownership while preserving these logical boundaries.

For control layers, see Layered Security Architecture.

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