01
Private AI infrastructure
Operate models on hardware and networks your organization controls.
- Ollama, vLLM and compatible runtimes
- Multiple models and role assignments
- Health, capacity and version monitoring
THE OBRENNA PLATFORM
The operating layer for organization-owned AI.
Bring private models, internal tools, central policy and a simple employee experience together—without moving your data plane into someone else's cloud.
02
Governed MCP integration
Connect internal systems without turning every employee into an infrastructure engineer.
- Streamable HTTP and local stdio
- Automatic discovery and schema review
- Per-tool confirmation requirements
03
Organization administration
Manage identity, access and machines from one consistent control plane.
- Owner, admin, member and auditor roles
- Secure invitations and session revocation
- Multiple environments and devices
04
Employee-ready desktop
Approved organization configuration arrives automatically after sign-in.
- No CLI, Python or JSON setup
- Visible models and permitted tools
- Safe failure and clear offline states
05
Privacy by architecture
The control plane handles governance while private work remains local.
- No prompt storage by default
- Opaque credential references
- Configurable retention and telemetry
06
Policy and audit
Make agent permissions understandable, reviewable and enforceable.
- Read, network, write and destructive risk
- Never, first-use or every-use confirmation
- Redacted decision history
RUNTIME FLEXIBILITY
Your models. Your hardware. One governed service.
Register endpoints without exposing runtime credentials to employees or the browser.
Ollama vLLM Compatible API
Production inference AVAILABLE
- Runtime
- vLLM 0.9
- Model role
- Primary reasoning
- Context limit
- 128,000 tokens
- Credential
- secret://prod/vllm
- Policy revision
- v42 · approved