Autoheal
Autoheal is an AI SRE platform purpose-built for regulated enterprises. It connects your observability, infrastructure, code, tools, and tribal knowledge into a unified Production Context Graph (PCG), then uses multiplayer AI agents to investigate issues, find root causes, and prevent them from happening again.
Additionally, it combines an on-call paging, an incident response bot, and a standalone AI SRE into a single platform.
Three Use Cases, One Platform
Normalizes and deduplicates alerts, gathers real-time diagnostic signals, and conducts deep-dive investigations with decision traces.
Manages incident channels, coordinates parallel team investigations, generates 5-Why RCAs, and surfaces preventive fixes.
Automate any SDLC workflow step with custom agents that run on your triggers, reason over production context, and report into your tools.
How It Works
When something goes wrong, Autoheal queries your observability stack (Datadog metrics, Grafana dashboards, Sentry errors, GitHub deployments) and correlates the data. It searches logs, traces service dependencies, and identifies what changed.
The agent collects relevant signals: error spikes, latency changes, recent commits, configuration diffs. It builds a timeline of events and surfaces the data points that matter.
Based on the evidence, Autoheal generates hypotheses about what's causing the issue. It ranks them by likelihood and explains its reasoning through decision traces, so you can validate or redirect.
For each hypothesis, Autoheal proposes immediate fixes (rollbacks, restarts, config changes, scaling actions) based on your runbooks and past incidents. For code-level issues, it surfaces preventive fixes for your team to review.
After resolution, Autoheal captures a memory of what happened, the root cause, and how it was resolved, so the same issue is handled faster next time. It also surfaces proactive actions, concrete improvements like tuning a noisy alert or fixing a recurring root cause, to prevent the issue from recurring. Both feed back into the Production Context Graph.
Production Context Graph
The Production Context Graph (PCG) continuously connects four kinds of context:
- Infrastructure. Your services, dependencies, and topology.
- Code. Repositories, deployments, and recent changes.
- Tools. Observability, incident management, and documentation platforms.
- Tribal knowledge. Runbooks, past incidents, team expertise, and learnings.
The PCG self-learns from both humans and successful agent actions. Each investigation, memory, proactive action, and runbook update makes the graph richer and future investigations faster.
Core Capabilities
| Capability | Description |
|---|---|
| Production Context Graph | Unified graph connecting infrastructure, code, tools, and knowledge |
| Decision Traces | Transparent reasoning — every agent decision is documented with the "why" |
| Adversarial Agent Review | Findings are validated through adversarial review for evidence-backed accuracy |
| Alert Deduplication | Normalizes, deduplicates, and categorizes incoming alerts automatically |
| Multi-turn Conversations | Work through complex investigations interactively with full context |
| Preventive Fixes | Identifies code-level root causes and surfaces preventive fixes for your team |
| Root Cause Analysis | Structured 5-Why RCAs with timeline, impact, root cause, and preventive measures |
| Knowledge Evolution | Learnings from each investigation feed back into the PCG |
The Feedback Loop
Every investigation makes Autoheal smarter:
Issue occurs → Agent investigates → Team resolves
↓
Agent learns ← Memories & proactive actions captured in Production Context Graph
When the agent asks "which dashboard should I check?" or "who owns this service?", that's a gap in your Production Context Graph. Fill it, and the next investigation is faster.
Memories from past incidents inform future ones. The skill that worked gets referenced. The hypothesis that was wrong gets deprioritized. Your institutional knowledge compounds.
Enterprise Ready
Isolated environments per organization. Your data never crosses tenant boundaries.
Admin and Member roles with granular permissions over integrations and Production Context Graph.
Enterprise single sign-on via OIDC/OAuth2. Works with Okta, Azure AD, Google Workspace.
Every investigation, every change, and every access is logged and queryable.