An open future for governed AI. Built in the open
Platform

Policy

Put policy in the graph.
Where work happens.

Design governance as visible operational context for tools, connectors, data, environments, approvals, and consequential agent requests.

Product direction · In active development

01

Policy belongs near capability

Policy requirements can be associated with agents, skills, workflows, connectors, environments, data classes, and deployment targets.

Concrete controls

Planned controls include tool access, sensitive data, external communication, infrastructure mutation, financial operations, secrets, and time windows.

02

Treat changes as operations

The intended lifecycle is draft, diff, simulate, review, approve, stage, roll out, observe, and roll back.

Impact before rollout

A policy change should reveal affected capabilities, changed approvals, exceptions, and simulation evidence.

03

A foundation, not a claim

Rangoon is designed around LNSAT for execution authorization and evidence, with planned policy-engine adapters alongside it.

Integration honesty

OPA, Cedar, and other policy-engine integrations are not claimed as shipped.

The future is open

More capability.
Greater possibilities.

Let’s build an AI ecosystem worth trusting.

Rangoon, the smiling orange crab mascot
Product previewConcept interface · sample data · active development

Explore the design. Actual interfaces and feature availability may evolve.

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