OnCall Owl

Your AI
On-Call Engineer.

Resolves incidents before you wake up.
Investigates, triages, and reports with evidence.

OnCall Owl — Investigation #417
Payment Service Incident
3:12 AM
CRITICAL Payment service error rate spiked
Investigate
Owl
New Relic — 23% error rate
PostgreSQL — "too many clients already"
GitHub — deploy at 2:15 AM added 3 DB connections
Root Cause
Owl
DB connection pool exhausted
2:15 AM deploy exceeded PostgreSQL limit
Approval Required
4:32

Rollback payment-service to v2.4.1 via GitHub

Resolved
Owl

Rolled back to v2.4.1. Error rate down to 3% and falling.

Owl plugs into your existing stack
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Everything an On-Call Engineer Does, at 10x Speed

Detects and investigates autonomously
Reads logs, metrics, and code changes in parallel. No context-switching.

Investigating...3:12 AM
New Relic
23% error rate
PagerDuty
3 alerts today
GitHub
2 deploys found
PostgreSQL
querying logs...
4 tools queried in parallel3 of 4 complete

Reports with evidence, not assumptions
Every finding cites its source with structured summary and confidence scoring.

Owl Report#417
Critical
Root Cause

Config deploy removed connection pool limits, causing exhaustion

Affected

payment-service, checkout-api

Confidence
High
Evidence
New Relic: error rate 4% → 23% at 3:04 AM
GitHub: pool_config.yml changed in deploy #1847
PostgreSQL: "too many clients" at 3:06 AM
Recommendation

Rollback deploy #1847 to restore pool size limits

Connects to your stack once
Runbooks, wikis, and tools — Owl learns your full on-call system.

Acts only with your approval
Queries autonomously. Rollbacks and deploys wait for you.

Approval Required4:58 remaining
Action

rollback_deploy

Parameters
service: payment-service
target: deploy #1846
reason: pool_config.yml regression

Every investigation searchable
Browse past incidents, compare patterns. Nothing lost in Slack threads.

Search past investigations...142
#421Medium
Today, 9:14 AM

Redis memory spike — cache eviction storm

#420Critical
Yesterday, 2:31 AM

Auth service 502s — expired TLS cert

#417Critical
Feb 6, 3:04 AM

DB pool exhaustion — config deploy regression

#415Low
Feb 4, 11:22 PM

Stripe webhook timeout — rate limit hit

142 investigationsMTTR down 64%

Notifies your team on resolution
Summary to Slack with root cause, evidence, and next steps.

#incidents3:18 AM
🦉
OnCall OwlAPP3:18 AM

Resolved: DB pool exhaustion

Severity

Critical

Duration

14 min

Confidence

High

Root Cause

Deploy #1847 removed connection pool limits

Action Taken

Rolled back to deploy #1846 ✓

View full report →
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Much like Cursor brought an AI copilot that reads and reasons about codebases in real time — OnCall Owl does the same for incidents. 90% fewer war room hours.
Sharath Keshava Narayana avatar
Sharath Keshava Narayana
CEO, Sanas

Hire your AI on-call engineer

From teams with a single on-call rotation to enterprises with
hundreds of services. Owl scales with your squad.

Junior
$0
/month
1 AI engineer working 1 shift. Designed for small on-call rotations.
Get Started today:
Real-time code suggestions
Basic integration logos
Single MCP server connection
Up to 2 AI coding agents
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Senior
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$350
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Multiple AI engineers, round-the-clock shifts. Designed for large teams.
Everything in Junior +
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Collaborative coding with team chat
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Priority email and chat support
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Everything in Junior +
Dedicated account support
Unlimited MCP server clusters
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Priority deployments and SLA guarantees

The Owl Effect

Here's what changes when Owl joins your on-call rotation.

<5 min
from incident to root cause
Cut your MTTR from hours to minutes.
— Anonymous, Early Adopter
Every
incident gets a full investigation
Not just the P0s. Every single one.
— Anonymous, Early Adopter
Zero
engineers needed for initial triage
Owl triages, you decide.
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90%
fewer war room hours
Your team focuses on fixing, not finding.
— Anonymous, Early Adopter
24/7
coverage without burnout
No more 3 AM pages. Owl never sleeps.
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Full
evidence trail on every finding
Tool name, timestamp, and exact data point. No hallucinations.
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Frequently Asked Questions

Everything you need to know about OnCall Owl

What is OnCall Owl?
OnCall Owl is an autonomous AI agent that investigates production incidents in real time. It connects to your observability tools, queries logs, metrics, and deploys in parallel, and delivers a root cause report with evidence — before your engineer even opens a laptop.
How does Owl investigate incidents?
When an alert fires, Owl queries all connected tools simultaneously — APM, logs, deployment history, database metrics. It correlates signals across sources, identifies the root cause, and produces a structured report with confidence scoring and cited evidence.
What tools does Owl integrate with?
Owl connects to PagerDuty, New Relic, Datadog, Sentry, GitHub, PostgreSQL, Slack, and more. Setup takes minutes — just provide API keys and Owl starts learning your stack. New integrations are added regularly.
Can Owl take actions like rollbacks?
Owl runs read-only queries freely, but any write action — rollbacks, deploys, config changes — requires your explicit approval. You see the full parameters before anything executes, with a 5-minute auto-timeout as a safety net.
Does Owl replace my on-call engineers?
No. Owl handles the triage and investigation so your engineers can focus on fixing. Think of it as a tireless first responder that gathers all the context, so when your team does get paged, they already know exactly what happened.
Is my data secure?
Yes. Owl runs on your infrastructure with end-to-end encryption. Credentials are stored in your own secrets manager. No incident data leaves your environment. Enterprise plans include SOC 2 compliance and custom deployment options.

Your next on-call engineer never sleeps

We're onboarding teams with 50+ engineers. See Owl investigate a real incident in your stack.