Nirmata AIControls
AIControls is a governance layer that sits between your developers and their AI tools — visibility, cost control, and policy enforcement on every AI call, without changing how developers work.
What it does
AIControls intercepts two types of traffic from AI coding tools (Claude Code, Cursor, Codex, Copilot): LLM calls to model APIs (Anthropic, OpenAI, Azure OpenAI, Bedrock) and MCP tool calls to backend servers (bash, file system, kubectl, databases, and any custom MCP server). Both pass through the same governance pipeline before reaching their destination:
- Identity — every request is authenticated and attributed to a developer or agent via your IdP or workspace tokens.
- Policy enforcement — CEL-based rules allow, deny, mutate, or route requests for human approval, evaluated inline.
- Content safety — PII, secrets, and prompt injection patterns are detected before tokens are sent.
- Budgets — spend limits per organization, team, or developer, enforced at request time.
- Audit log — every prompt, tool call, response, model, token count, and policy decision recorded.
- Intelligence — session summaries, behavioral baselines, anomaly detection, risk scores, and context optimization that reduces token waste.
How it works
Your workspace comes with a proxy endpoint. You configure each AI tool to route through that endpoint instead of calling the provider directly. AIControls holds your API keys — developers use workspace-issued credentials, so provider keys never live on developer machines.
No agents to install. No SDKs to integrate. One endpoint, all tools.
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