AxonFlow: Runtime control layer for production AI
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Updated
Aug 26, 2026 - Go
AxonFlow: Runtime control layer for production AI
Make AI coding agents safe to scale autonomously: assign work, cap spend, enforce policy, verify output, roll back failures, learn from loops, and prove ROI across every repo.
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
AxonFlow governance for Claude Code — block dangerous commands, govern MCP queries and command execution, and keep audit trails for production coding agents
Independent verifier for signed AI audit exports and Permit-spec evidence
Open AI Permit specification for pre-execution action authorization records
Official Go SDK for the Keel AI control plane
AxonFlow governance for Cursor IDE — block dangerous commands, govern MCP queries and command execution, and keep audit trails for production coding agents
Vidai — the AI control plane. Govern, cost and secure every enterprise LLM request, from within your own network. Self-install Docker releases.
AxonFlow governance for OpenAI Codex — enforce policy on terminal actions, add governed MCP checks, and keep audit trails for production coding agents
Official Terraform provider for the Keel AI control plane
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.
Three practical examples of AI guardrails: LLM guardrails, agent tool-calling authorization, and multi-agent governance patterns for enterprise AI systems.
Open source AI sovereignty router for controlling where AI workloads run, where data goes, and how model execution is governed.
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
Official Java SDK for AxonFlow — runtime control, MCP policy enforcement, approvals, and audit trails for production AI
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