ai-control-plane

Run coding agents without babysitting them. Keep jobs focused, bounded, checked and accountable from start to finish. Finally run your agents swarms overnight and get your time back.

AxonFlow: Runtime control layer for production AI

Chronos - self-hosted, MCP-native control plane for AI agents. Build agents visually or register external ones; broker every tool through one audited MCP gateway.

The open-source control plane for AI agents — skill routing, context governance, trustworthy execution, evidence, security, and multi-agent orchestration.

AxonFlow governance for OpenClaw agents — block dangerous tools, govern MCP access, and keep audit trails for production agent workflows

Vidai — the AI control plane. Govern, cost and secure every enterprise LLM request, from within your own network. Self-install Docker releases.

Independent verifier for signed AI audit exports and Permit-spec evidence

AxonFlow governance for Claude Code — block dangerous commands, govern MCP queries and command execution, and keep audit trails for production coding agents

Open AI Permit specification for pre-execution action authorization records

AxonFlow governance for Cursor IDE — block dangerous commands, govern MCP queries and command execution, and keep audit trails for production coding agents

Official Go SDK for the Keel AI control plane

Official Terraform provider for the Keel AI control plane

AxonFlow governance for OpenAI Codex — enforce policy on terminal actions, add governed MCP checks, and keep audit trails for production coding agents

ACR Control Plane: runtime control & governance for agentic AI (six-pillar enforcement).

Advanced, modular, and enterprise-grade AI automation control plane combining Custom GPT Actions, n8n orchestration, Google Workspace workflows, and serverless OCR. Implements schema-driven, agent-based ingest, clean, analyze, and report pipelines with data normalization, conversion, audit logging, cron-based scheduling, & enterprise observability.

Open source AI sovereignty router for controlling where AI workloads run, where data goes, and how model execution is governed.

Official Java SDK for AxonFlow — runtime control, MCP policy enforcement, approvals, and audit trails for production AI

Three practical examples of AI guardrails: LLM guardrails, agent tool-calling authorization, and multi-agent governance patterns for enterprise AI systems.

Official Python SDK for AxonFlow — runtime control, MCP policy enforcement, approvals, and audit trails for production AI

Official TypeScript SDK for AxonFlow — runtime control, MCP policy enforcement, approvals, and audit trails for production AI