Synap Intelligence
Managed orchestration and policy layer for agents on top of your pod, with a bring-your-own option
Synap Intelligence is not only a model endpoint.
It is the layer that lets AI operate on pod data with governance.
What it adds on top of models
- Pod-native context: agents use the same entity/view/channel model as user-facing apps
- Governed actions: proposal-first mutation flow for operations requiring review
- Consistent integration contract: Hub Protocol as the stable surface for agent/tool operations
- Operational controls: access lifecycle, usage controls, and service-level management in hosted mode
Managed Synap Intelligence vs your own service
| Option | Best for | Trade-off |
|---|---|---|
| Managed Synap Intelligence | teams that want fastest setup and lower ops burden | less runtime-level customization |
| Self-managed Intelligence Service | teams that need custom runtime, hosting, and service internals | you own deployment, uptime, and service operations |
Both options still rely on the same pod-centric model and governance principles.
Public decision guide
Use managed Intelligence when you want:
- quick activation
- minimal infra operations
- predictable integration path with Synap Cloud
Use self-managed Intelligence Service when you need:
- custom deployment/runtime behavior
- stricter control of hosting/network boundaries
- deeper service-level customization