AI Engineer That Reads Your Logs.
Pipe your application logs to SipSip AI. It detects anomalies, explains errors in plain English, identifies root causes, and surfaces recommended actions — before your users notice and before your on-call engineer has to piece it together alone.
[ERROR] 2026-04-04 07:14:23 — ConnectionPoolTimeoutError
[WARN] Retry 1/3 failed — upstream timeout after 5000ms
[ERROR] 2026-04-04 07:14:28 — 503 Service Unavailable
[INFO] Circuit breaker opened after 5 consecutive failures
[ERROR] 2026-04-04 07:14:33 — Queue depth: 2847 (threshold: 500)
🚨 AI Alert — Root Cause Identified
Database connection pool exhausted due to a long-running migration query started at 07:09. The migration locked table transcription_jobs, causing upstream timeouts that triggered the circuit breaker. Queue backlog is 2,847 items.
Recommended Actions
- 1.Kill migration query PID 4821 to release table lock
- 2.Scale connection pool from 20 → 50 as immediate mitigation
- 3.Drain queue backlog before re-enabling circuit breaker
What's included
Everything you need
Log ingestion
Connect via log streaming, file upload, or API. Works with any log format — structured JSON, plain text, or standard log levels (ERROR, WARN, INFO).
Anomaly detection
SipSip AI learns your normal error baseline and alerts on deviations — spike in 5xx errors, latency outliers, unusual queue depth, or sudden silence from a service.
Plain-English explanations
Every alert includes an AI-generated explanation of what happened and why — in language your whole team can understand, not just the engineer who wrote the service.
Root cause analysis
AI traces error chains across services, correlates timestamps, and identifies the originating failure — not just the symptom that triggered the alert.
Automated alerting
Alerts route to Slack, PagerDuty, email, or Discord the moment an incident is detected — with the AI explanation already attached, so on-call has context from the first ping.
Incident summaries
After resolution, SipSip generates an incident report: timeline, root cause, impact, and recommended follow-ups. Post-mortems write themselves.
Simple by design
How it works
Connect your log source: stream logs via webhook, agent, or file upload. SipSip accepts any structured or unstructured log format.
SipSip AI establishes your baseline — normal error rates, latency distributions, and service behavior — over the first 48 hours.
When an anomaly is detected, SipSip immediately analyzes the surrounding log context to identify the root cause.
An alert fires to your configured channel (Slack, PagerDuty, email) with a plain-English explanation attached — not just a raw error.
On-call engineers get the diagnosis alongside the alert. No more 20-minute log triage before you know what's actually broken.
After resolution, SipSip generates a complete incident report: timeline, root cause, blast radius, and recommended preventions.
Real users, real results
Who uses Incident Intelligence
Our on-call rotation used to mean 30 minutes of log diving to understand what actually broke. Now the alert comes with a root cause analysis attached. I fix instead of investigate.
SipSip generates a draft timeline and root cause summary automatically. I spend 10 minutes reviewing instead of 3 hours writing incident reports.
We don't have a dedicated SRE. SipSip is the closest thing to one — it watches the logs, explains what goes wrong, and tells the team what to do about it.
The plain-English explanations changed how we handle incidents. Non-engineers can understand the alert, which means I don't have to make triage decisions at 2am.
Frequently asked questions
Quick answers to common questions about Incident Intelligence.
AI incident intelligence analyzes logs and runtime signals to detect anomalies, explain incidents, and highlight likely root causes with suggested next actions.
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