
Neural Inverse Govern · Powered by Keystone
Every AI tool your engineers use, under one set of controls.
Govern decides who may use which model, what agents may do and who must approve it, for Neural Inverse Build and the third-party tools your teams already use. Every decision is recorded.
- For
- Security, compliance and platform teams
- Governs
- Neural Inverse Build and third-party AI tools
- Sign-in
- SAML, OIDC, passkeys and SCIM
- Enforced in
- Server-side gateways and a signed endpoint policy
- Deployment
- Self-hosted, your cloud or air-gapped
Overview
Govern is the control plane for the AI models, agents and tools your engineers use. It holds identity and access, decides what each person, agent and tool may do, enforces those decisions in its own gateways, and records every decision in an audit log your auditors can verify.
How Govern is built
Decisions are made on the server, and fail closed.
Identity and access
Every person and every agent is known.
Access follows your directory. Nobody holds more than they need, and nobody grants access to themselves.
AI Gateway
Approved models only, every request on record.
People, applications and agents reach models through one gateway inside Govern. Provider keys never leave it.
Agent policy and approvals
Allow, ask or deny. A person decides what matters.
One policy is written in Govern and compiled for each agent engine. The endpoint agent enforces it on the developer's machine.
Third-party AI tools
Govern the tools your teams already use, as far as each allows.
Govern compiles one policy into each tool's own controls and states plainly how far that reaches. Only an Enforced tool blocks reliably. The levels assume the endpoint agent has installed the compiled policy in the tool's managed location; they were verified against each vendor's mechanism and version in October 2026.
| Tool | Control level |
|---|---|
| Claude Code | Enforced |
| Cursor | Enforced |
| Windsurf | Enforced |
| GitHub Copilot CLI | Enforced |
| Codex | In verification |
| Gemini CLI | Managed configuration |
| Kiro CLI | Monitored |
| Cline | Monitored |
| Amazon Q Developer | Monitored |
| Continue | Not controlled |
Claude Code, Codex, Aider, Continue, Cline and Roo Code can also send their model requests through the Govern AI Gateway, so model access, budgets, DLP and guardrails apply to them (Network). Cursor does so only for custom models. Without an egress lock on developer machines, a person can bypass the gateway with another key or endpoint.
Product names belong to their owners.
Context for agents
Agents work from approved knowledge only.
Teams decide which sources agents may draw on. Govern checks access on every retrieval and records what was used.
Audit and evidence
A record your auditors can check without trusting us.
Who did what, with which tool, under which rule and with whose approval, kept in one append-only log.
How a request moves through Govern
Checked, approved where it matters, and recorded.
Shown for a model request. Agent actions and MCP tool calls are identified, decided, approved and recorded the same way.
- IdentifyGovern establishes who is asking: a person, an agent, a gateway key or a workload, from a short-lived credential.
- DecidePolicy for that person or agent is applied: approved models, the project's classification, agent rules and deny rules.
- ProtectDLP and guardrails check the content; budgets and rate limits are reserved before anything is sent.
- ApproveAn action that needs a person waits for a named approver who is not the requester.
- RecordThe decision, the rule behind it and any approval are written to the hash-chained audit log.

Where it runs
Deploy it where your data has to stay.
Deployment optionsWorks with Neural Inverse Build
Give engineers AI that follows your rules from the first keystroke.
Build's Editor, Agents and CLI sign in with Govern, use models through its gateway and record their activity in its audit log.
Explore Build
Talk to our team.
Neural Inverse is available by request. We work with your engineering, security and procurement teams from the first conversation.