synapse

Purpose

Integrate intelligence into systems through retrieval, model calls, and workflow-level inference.

Why it matters

Without a clear AI layer, intelligence gets bolted on ad hoc and becomes difficult to trace, evaluate, or reuse.

Scope

This repo focuses on AI workflows, retrieval-aware service structure, and inference boundaries. It does not try to cover every model or vendor integration.

System Role

synapse is the AI and ML systems layer for the ecosystem. It connects data, knowledge, and product workflows through practical intelligence features.

System Connections

• Depends on: flux for prepared data and lore for grounded retrieval structure.
• Feeds into: product-facing intelligent features in summit and orbit.
• Interacts with: lore, summit, flux.

Core Concepts

• retrieval flow
• inference boundaries
• prompt inputs
• model orchestration
• grounded responses

Minimal Artifact

service/main.py, service/models.py, and docs/architecture.md form the starter AI service example.

Notes

The emphasis is on AI that fits into system design, not standalone demos with no operational shape.

Next Steps

Add provider adapters, evaluation hooks, and clearer retrieval interfaces.