Architecture

Ecosystem context

This repository is part of the Raven AI ecosystem:

Raven AI: flagship biology and healthcare agent platform.
OpenClinical AI: healthcare deployment layer and clinical workflow substrate.
Home for AI: local orchestration environment for agent workflows.

Architectural principles

Local-first where possible, cloud-optional where necessary.
Evidence-linked outputs for scientific and clinical work.
Explicit audit, provenance, and governance boundaries.
Modular adapters rather than hard-coded model or vendor lock-in.
Fail-loud behavior for privacy, safety, and policy violations.

High-level diagram

flowchart LR
  User[Researcher / Clinician / Operator] --> UI[Client UI]
  UI --> API[Runtime API]
  API --> Agents[Agent + Tool Layer]
  Agents --> Workflows[Workflow Engine]
  Agents --> Models[Model Adapters]
  Agents --> Evidence[Evidence + Data Sources]
  API --> Governance[Governance: audit, consent, provenance]
  Governance --> Logs[(Audit Logs)]
  Workflows --> Artifacts[(Reports / Results / Traces)]

Runtime layers

Interface layer: web, desktop, mobile, or CLI entry points.
Runtime layer: API routes, tenancy, auth, model/tool dispatch.
Agent layer: task planning, tool use, domain workflows.
Governance layer: consent, policy checks, audit logs, provenance.
Deployment layer: Docker, local runtime, cloud deployment, edge.

Current maturity

This repository may contain a mix of production-ready components and architectural previews. Components that touch clinical or biological decision-making must be treated as research/developer infrastructure until validated for the target context.