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Root Cause Analysis 2.0

AI Root Cause Analysis That Identifies the Exact Deploy

4-tier AI system that auto-selects the best model for each incident. Correlates deployments, detects cascading failures, and learns from every resolution.

Root Cause Analysis 2.0
4-TIER AI SYSTEM

The Right AI Model for Every Incident

Auto-selects based on incident severity, cascade detection, and deploy correlation

Basic

GPT-5-nano
4 credits

Quick triage and file-level identification for routine incidents.

Fast response for routine issues
File-level identification
Best Value

Standard

Claude Haiku 4.5
8 credits

Balanced analysis with historical pattern awareness. 95% confidence at optimal cost.

95% confidence, fastest premium model
Historical pattern detection

Deep

GPT-5
12 credits

Exact line identification with fix suggestions. Identifies up to 7 suspected lines.

Line-level code identification
Up to 7 suspected lines with fixes

Premium

Claude Sonnet 4.5
15 credits

Most actionable analysis with 7 prioritized actions and post-fix verification plan.

7 prioritized remediation actions
Post-fix verification plan
EVOLUTION

RCA 1.0 vs RCA 2.0

Capability
RCA 1.0
RCA 2.0
Scope
Individual monitor
Full service + cascade graph
Deploy Correlation
None
Exact commit SHA + file diffs
Cascade Detection
Metadata only
Full upstream verification
Learning
Static
Closed-loop with pgvector KB
Evidence
Unweighted text
Typed + numerical weights
Actions
Free text
Structured with urgency levels
DEPLOY CORRELATION

Deploy Correlation Engine

Automatically identifies which deployment caused which incident with weighted scoring

35%

TIME

Proximity between deploy and incident

30%

SERVICE

Same service match

20%

FILE

Changed files vs incident type

15%

PATTERN

Historical deploy-incident patterns

3-Phase Webhook Ingestion

1

Push Events

GitHub/GitLab push hooks with estimated timestamps

2

Deployment Status

Confirmed deployment with exact timestamps and status

3

Custom Webhook

Universal endpoint for any CI/CD pipeline

Closed-Loop Knowledge Base

RCA improves with every resolution through pgvector semantic search and feedback-driven learning.

pgvector semantic search on past incidents
Feedback updates effectiveness scores
User corrections become KB entries
FAQ

Frequently Asked Questions

Everything about Root Cause Analysis 2.0

Find Root Causes in Minutes, Not Hours

Let AI identify the exact deployment, code line, and cascade path causing your incidents.