AI SRE

Incident response that starts with answers

Reduce MTTR by connecting alerts, changes, and human insight with AI.

40%faster time to resolutionAcross all incident severities
100%automated timelineEliminates manual scribe work
Minutesto root cause hypothesisChange correlation at alert time
AI SRE Workflow

From alert to resolution and beyond

AI SRE understands your full delivery workflow across deployments, feature flags, infrastructure changes, and monitoring signals. Ask questions mid-incident for instant correlation, auto-documentation, and one-click remediation.

AI Scribe Automatic incident record across Slack, Zoom & Teams — zero manual note-taking.

AI Root Cause Analysis Correlates deploys, flags, infra & monitors in seconds to surface root cause instantly.

Automation Runbooks ServiceNow → Jira → GitHub → rollback → investigate in one chain. One-click remediation.

On-Call & Escalations Schedules, rotations & policies you own end-to-end — right person, every time.

Measurable outcomes

What changes when AI SRE is in the room

AI SRE shifts the metrics that matter: fewer interruptions, less manual work, and more confident responders.

On-call confidence goes up

Responders start with a full picture: ownership, recent changes, similar past incidents, blast radius, and a suggested starting hypothesis. No more blank-screen triage at 2 a.m.

Time to context collapses

Responders get logs, metrics, recent changes, ownership, and past incidents in one place at alert time. No more dashboard hunting in the first 20 minutes of an incident.

Unnecessary escalations disappear

The on-call engineer has enough context to act without immediately paging the service owner. Better information means fewer people pulled in unnecessarily.

Postmortems write themselves

The timeline, decisions, and action items are captured during the incident. Less writing after the fact, and the output is actually accurate.

Repeat incidents become rare

Recurring patterns become easier to spot, so teams can fix the root cause instead of fighting the same fire again.

Every incident tied to a change

Deploys, flags, config changes, and infrastructure events are automatically correlated and attached at alert time, with no manual digging through change records.

Runbook-driven, consistent resolution

Known failure patterns move from manual response to guided fixes, and eventually to full automation once trusted. Every incident handled consistently, not differently by whoever is on call.

Alert noise drops

Related alerts get grouped into real incidents. Fewer pages for the same problem, so on-call engineers spend time on real work, not duplicate notifications.

Full platform capabilities

Let AI handle the busy work while your team solves what matters

Complete incident response from detection through documentation and resolution, powered by AI and integrated with your existing tools.

Change Intelligence

Automatically correlates deploys, flags, and config changes to surface likely causes.

Live Incident Timeline

Builds a real-time, shared timeline from alerts, logs, chats, and meetings.

Smart On-Call & Escalation

Routes incidents using live schedules, ownership, and severity policies.

AI Scribe

Captures decisions, actions, and context automatically, eliminating retroactive RCA writing.

Automation Runbooks

Safely rollback, mitigate, or fix forward with trusted automation.

Unified ingestion & automation

Pulls in alerts, tickets, deploys, flags, and events from all your tools.

Built for every role

AI SRE for your whole team

Scale response without scaling team

AI Scribe automatically documents incidents from Slack and Zoom, eliminating manual note-taking

Root cause analysis correlates changes across deployments, flags, and infrastructure in seconds

Automation runbooks standardize first response and reduce MTTR consistently

Use cases

Real-world incident scenarios

How teams use AI SRE to cut through noise, find cause, and respond safely.

Noisy alert storms

Use change context to collapse duplicates and focus on the event that matters.

Unexpected failures

Use recent change context to narrow scope, identify what changed, and determine likely cause.

War-room accuracy

Let Scribe handle notes, decisions, and the action audit trail.

One-click remediation

One-click runbooks to roll back, scale out, or toggle a feature flag.

Customer success

Proven incident response acceleration

AI Scribe eliminated hours of manual postmortem writing. It captures everything from our Slack channels and generates comprehensive incident reports automatically.

Principal Engineer, SaaS Platform

Change correlation is a game changer. Instead of manually checking deploy logs and feature flags during incidents, AI SRE surfaces exactly what changed and when.

Senior SRE, E-commerce

Automation runbooks reduced our MTTR by 40%. Standard remediation steps now execute automatically, and our on-call team sleeps better.

Engineering Manager, Fintech

Integrations

Built for your incident ecosystems

Connect your entire incident response stack: alerting, observability, communication, and ticketing, all working together with AI.

Microsoft Teams
Microsoft Teams
Datadog
Datadog
Slack
Slack
Jira
Jira
ServiceNow
ServiceNow
Splunk
Splunk
New Relic
New Relic
Dynatrace
Dynatrace
GitHub
GitHub
FAQs

Frequently asked questions

AI Site Reliability Engineering applies artificial intelligence and machine learning to automate and improve system reliability, monitoring, incident response, and operational tasks.

AI analyzes patterns in logs and metrics to detect anomalies faster, predicts potential failures before they occur, and suggests remediation steps based on historical incident data.

Traditional SRE relies on manual processes and rule-based automation, while AI SRE uses machine learning to adapt, predict issues, and automate complex decision-making at scale.

Common use cases include anomaly detection, predictive alerting, automated root cause analysis, capacity planning, intelligent incident triage, and self-healing systems.

No. Harness AI SRE connects to the alerting, observability, and ticketing tools you already run, so a small team can start with one service and a single use case such as change correlation or automated incident documentation, then expand coverage as trust builds.

Yes! Harness On-Call offers like-for-like functionality with PagerDuty, OpsGenie, and xMatters, including on-call scheduling and escalation support. We also make it easy to switch — you can quickly import your existing setup directly from PagerDuty, OpsGenie, or xMatters so you're up and running with minimal disruption.

Get started with Harness AI SRE

Book a personalized demo and watch AI SRE triage a live incident, surface root cause from real change data, and run remediation across the tools your team already uses.