Omnirelm
AI-powered SRE copilot that handles incidents
so your teams don't have to scramble.
AI-Powered Reliability. Delivered Quietly.
Define agents, build workflows, and let Omnirelm orchestrate incident investigation for your team.
Learn about orchestrationYou Have Monitoring.
But You're Still on Fire.
How Incident Response Changes with Omnirelm
| Dimension | Before Omnirelm | With Omnirelm SRE Agent |
|---|---|---|
Cognitive Overload | Engineers manually correlate alerts, logs, metrics, and traces across multiple tools to estimate blast radius and possible root causes 10–15 minutes | Agent automatically correlates telemetry, service dependencies, and recent changes to determine impact scope and surface top likely failure points 5–10 seconds |
Incident Coordination | Manual incident channel setup and ad-hoc responder coordination based on tribal knowledge 5–10 minutes | Incident bridge created automatically, responders auto-selected using service ownership, and relevant context shared upfront Seconds |
Mean Time to Diagnose (MTTD) | Engineers pivot across 5–10 dashboards to manually narrow down the failing service, dependency, or recent change 30–40 minutes | Agent analyzes signals and highlights the most likely failure area with supporting evidence 5–10 seconds |
Mean Time to Recovery (MTTR) | Recovery slowed by manual diagnosis, repeated handoffs, and lack of shared context 60–120 minutes | Faster diagnosis, aligned responders, and reduced handoffs enable quicker mitigation and recovery 25–45% lower MTTR |
Context & Confidence | High uncertainty during early response; decisions made with incomplete or fragmented information | Early, evidence-backed hypotheses provide shared understanding and higher confidence in recovery actions |
Cognitive Overload
Before Omnirelm
Engineers manually correlate alerts, logs, metrics, and traces across multiple tools to estimate blast radius and possible root causes
With Omnirelm SRE Agent
Agent automatically correlates telemetry, service dependencies, and recent changes to determine impact scope and surface top likely failure points
Incident Coordination
Before Omnirelm
Manual incident channel setup and ad-hoc responder coordination based on tribal knowledge
With Omnirelm SRE Agent
Incident bridge created, relevant responders auto-selected based on service ownership, and context shared upfront
Mean Time to Diagnose (MTTD)
Before Omnirelm
Engineers pivot across 5–10 dashboards to manually narrow down the failing service, dependency, or recent change
With Omnirelm SRE Agent
Agent analyzes signals and highlights the most likely failure area with supporting evidence
Mean Time to Recovery (MTTR)
Before Omnirelm
Recovery slowed by manual diagnosis, repeated handoffs, and lack of shared context
With Omnirelm SRE Agent
Faster diagnosis, aligned responders, and reduced handoffs enable quicker mitigation and recovery
Context & Confidence
Before Omnirelm
High uncertainty during early response; decisions made with incomplete or fragmented information
With Omnirelm SRE Agent
Early, evidence-backed hypotheses provide shared understanding and higher confidence in recovery actions
Built to Think. Ready to Act.
Omnirelm doesn't just alert you.
It understands your system and the problem as well.
AI-Led RCA Suggestion
- Instant incident summary
- High-confidence root cause identification
- Dependency-aware insight across services
- Automated blast radius assessment
Works with your existing systems
- Plug-and-play integration with your existing monitoring tools, APM, etc.
- Connects effortlessly to collaboration platforms like Slack.
- Correlates recent commits from GitHub to surface deployment-related root causes.
Incident Collaboration
- Unified Incident Timeline
- AI-Summarized Incident Context
- Notifications & Handover
- Human-in-the-Loop RCA Feedback
Agent Orchestration
- Agents tailored to your investigation steps
- Workflows that chain those steps together
- Orchestration handled by Omnirelm
Agents and Workflows, Built Your Way
Define the agents and workflows that fit how your team investigates incidents. Omnirelm handles the orchestration so you can focus on resolution.
Agents
Specialized agents, each built for one job.
into
Workflow
Agents chained in sequence to investigate an incident.
Agents
Workflow
Define your agents
Create focused AI agents for the jobs your team does during incidents — querying logs, analyzing traces, reviewing code, and more.
Build workflows
Chain agents into step-by-step workflows so investigation moves from signal to insight without manual handoffs.
Integrations
Works seamlessly with your existing observability and collaboration tools
Loki
OpenSearch
Jaeger
Tempo
Slack
GitHub
From Alert to Action
How Omnirelm Handles Incidents
Detect
Listens for alerts from your existing monitoring systems.
Diagnose
Analyses logs and telemetry data from your APM platform to identify root cause.
Contextualize
Creates incident context with telemetry, recent code changes, and an AI-generated RCA summary.
Collaborate
Helps on-call engineers to triage incidents and get instant clarity.
Detect
Listens for alerts from your existing monitoring systems.
Diagnose
Analyses logs and telemetry data from your APM platform to identify root cause.
Contextualize
Creates incident context with telemetry, recent code changes, and an AI-generated RCA summary.
Collaborate
Helps on-call engineers to triage incidents and get instant clarity.
Frequently Asked Questions
Quick answers about Omnirelm and how it helps on-call teams.
What is Omnirelm?
Does Omnirelm replace our existing monitoring tools?
What data does Omnirelm use during an incident?
Is Omnirelm open source?
Can I define my own agents and workflows?
Built in the Open. Shaped by You.
In active development. Open to ideas. Join us early — as a user, contributor, or both
Shape Omnirelm