Autoheal actively investigates alerts, hypothesizes root cause, and proposes mitigating fixes under human supervision. It also automates the postmortem phase completely. At its core is the Production Context Graph (PCG), a continuously updating, living map that connects your infrastructure, application logic, production tools and tribal knowledge in real-time. The PCG is built through autonomous exploration of your observability, cloud and code stack, and iteratively refined by a Reinforcement Learning loop as you use Autoheal. On top of the PCG lies a Multi-Agent Platform of specialized agents that collaborate with humans to solve production problems safely and efficiently.
For AI agents focused on production engineering to succeed in real-world enterprise deployments, three crucial gaps must be addressed.
The Context Gap: can the AI navigate my organization’s fragmented context?
The Trust Gap: can I trust the AI to strictly adhere to my organization’s security policies?