Open Source
Free
- Full AI features
- All 300+ integrations
- Apache 2.0 license
- Self-hosted
IncidentFox: Engineering Analytics
Founded 2025|San Francisco, CA|2-10 people|Open Source
What is IncidentFox?
IncidentFox is an open-source AI SRE platform that automatically investigates production incidents end-to-end. Part of YC W2026, it was founded by Chiehmin (Jimmy) Wei (ex-Roblox, ex-Meta FAIR) and Long Yi (ex-Roblox), both with experience building distributed systems serving millions of users.
When an alert fires, IncidentFox kicks off an investigation within Slack threads — querying logs, checking pod status, correlating with recent deployments — and delivers root cause analysis with executable fix scripts. The platform ships with 300+ prebuilt integrations covering Kubernetes, AWS, Grafana, Prometheus, Datadog, Elasticsearch, PagerDuty, and GitHub. It auto-discovers each team's stack and generates needed integrations, reducing setup from months to under a day.
The system uses multi-agent orchestration routing specialist agents to sub-problems, intelligent log sampling (statistical analysis before targeted fetching), and 3-layer alert correlation (temporal, topology, semantic) that reduces alert noise by 85-95%. It supports 24+ LLM providers and can be deployed as SaaS, on-prem/VPC, or fully self-hosted. The core is Apache 2.0 licensed with full feature parity on the free tier.
Key features
Core capabilities this platform advertises.
- Auto-incident triage
- Slack/Teams integration
- Log querying
- Deploy correlation
- Root cause identification
- 300+ tool integrations
Strengths and tradeoffs
What this tool does well, and the limitations to keep in mind.
Pros
- Genuinely open source (Apache 2.0) with full feature parity — no artificial limitations on free tier
- 300+ prebuilt integrations with auto-discovery reducing setup from months to under a day
- Intelligent log handling with statistical sampling solving the LLM context window limitation
- 85-95% alert noise reduction through 3-layer temporal, topology, and semantic correlation
- Flexible deployment across SaaS, on-prem, and self-hosted with 24+ LLM provider support
Cons
Plans & pricing
What's included in each plan, and how the tiers compare.
Enterprise
Custom
Contact sales for a quote
Common use cases
SRE and DevOps teams
- Incident response automation
- Root cause analysis
- On-call support
- Deploy monitoring
Using IncidentFox with Respan
IncidentFox investigates production incidents across infrastructure, while Respan monitors AI/LLM-specific issues. Together they provide comprehensive incident response covering both traditional infrastructure and AI application layers.
- Correlate LLM performance issues detected by Respan with infrastructure incidents in IncidentFox
- Surface AI-related production issues through Respan for IncidentFox to auto-investigate
- Use IncidentFox alert correlation alongside Respan LLM monitoring for full-stack visibility
Run IncidentFox in production with Respan
10KFree traces/mo
500+Models
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Last verified: March 27, 2026
