Autoheal
AI for Production Engineering. The first AI platform leveraging a Production Context Graph to accurately triage, investigate, and heal your production systems in the most demanding enterprise environments.
What Is Autoheal?
Autoheal is an AI platform purpose-built for production engineering. It connects your 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.
Unlike stitching together an on-call tool, an incident response bot, and a standalone AI SRE, Autoheal delivers all three natively in 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.
Automatically investigates customer support tickets, posts findings, and resolves issues without escalating to engineering.
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 produces a structured 5-Why RCA: what happened, why it happened, the timeline, impact, and preventive measures. This feeds back into the Production Context Graph, so the same issue is resolved faster next time.
Production Context Graph
The Production Context Graph (PCG) is what makes Autoheal fundamentally different from bolt-on AI tools. It continuously connects:
- Infrastructure — your services, dependencies, and topology
- Code — repositories, deployments, 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. Every investigation, every RCA, every 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 ← RCA 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, every access—logged and queryable.