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Autoheal

Autoheal provides an AI‑driven Site Reliability Engineering platform designed for regulated enterprises, offering a zero‑trust agentic runtime that autonomously investigates and remediates incidents while maintaining fine‑grained policy controls and full audit trails.

San Mateo, United StatesFounded 202511500+ followers
Updated 2 months ago

Funding

Funding not disclosed

Funding rounds are not available yet.

Founders

Founder details are not available yet.

Product

Problem

Regulated enterprises face high downtime costs, on‑call engineer burnout, and frequent skipped postmortems because traditional SRE processes rely on manual alert triage, fragmented knowledge, and SaaS tools that cannot meet strict compliance and data‑sovereignty requirements.

Solution

Autoheal delivers an AI‑driven Site Reliability Engineering platform built specifically for regulated environments. Its zero‑trust agentic runtime executes investigation and remediation actions autonomously while enforcing fine‑grained policy controls and providing a complete audit trail. A production context graph continuously maps services, dependencies, and team ownership, instantly supplying responders with full system state and decision traces. The platform refreshes runbooks with historical incident data, enabling multi‑hypothesis, evidence‑based troubleshooting that reduces mean time to detection (MTTD) and mean time to recovery (MTTR) from hours to minutes. Deployment runs inside the customer’s own cloud account, keeping all data and large‑language‑model inference on‑premise to satisfy data‑sovereignty and compliance mandates.

Target Audience

Primary customers are SRE and reliability engineering teams within regulated industries such as finance, healthcare, and telecommunications that require strict compliance, data sovereignty, and scalable incident automation.

Features

  • Zero‑trust agentic runtime with declarative policy controls, approval gating, and full audit logging
  • Production Context Graph that auto‑discovers services, dependencies, and team ownership, and records decision traces
  • AI agents that generate investigation skills and multi‑hypothesis root‑cause hypotheses before human paging
  • Runbook automation that enriches standard operating procedures with historical incident data
  • Bring‑Your‑Own‑Cloud deployment with in‑perimeter LLM inference and optional air‑gapped operation
  • Encryption with customer‑managed KMS keys and streaming of audit logs to existing SIEM solutions
  • Integration hooks for Slack, Microsoft Teams, and common monitoring platforms to enable collaborative incident response
This profile is AI-generated and may contain inaccuracies.