High confidence
JiraToolConfig was updated without a migration — GET /api/external-tools/{id}/config returns schema 2.1 but callers expect 1.4, causing silent null failures on auth_method.
The AI SRE
The AI SRE Built for the Unknown
RunLLM predicts issues before alert thresholds fire, investigates without runbooks, and resolves novel incidents.
INVESTIGATION-2847 / hypotheses 14:23 PST
Real investigation on RunLLM production; sensitive details redacted. See more
Trusted in Production
Why other AI SREs don't work
High Maintenance. Poor Coverage.
The metric stays below the alert threshold for most of the chart, then crosses it. Marker 1 identifies the threshold crossing. The area above the threshold after that crossing is labeled no runbook coverage, and marker 2 identifies the uncovered alert territory.
1 threshold model
Others Require Alert Thresholds
You have to instrument, tune thresholds for each data stream, and anticipate every failure mode worth watching. Miss one, and you're blind to it.
2 runbook coverage
Others Require Runbooks
You document every investigation workflow before it's needed. Maintain them as your stack evolves. When something novel breaks, there's no runbook and no investigation.
Every other AI SRE is purely reactive — and only handles failures someone already anticipated.
THE RUNLLM APPROACH
Stop reacting. Start preventing.
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Learn
RunLLM builds a context graph before any alerts fire — observability, codebase, CI/CD, docs, and dependencies — so it knows what normal looks like and can work to solve any problem.
context: Jira tool 65 · config read path ·
CUST-8291-X -
Detect
No thresholds to set. RunLLM builds a custom anomaly detection model for each data stream and surfaces validated issues before your customers notice.
validated signal: HTTP 500s rose to 18–26% over 22 minutes while other tenants stayed flat
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Investigate
Never write another runbook. RunLLM evaluates multiple hypotheses simultaneously, each against the right data source, and delivers RCAs in minutes.
RCA: Schema Drift · legacy Vault keys rejected after
PR #4275
In Production
Results. Delivered Fast.
RunLLM's agent onboards and adapts quickly. Gartner's 2026 AI SRE Market Guide identifies proactive incident prevention and contextual awareness as next-generation capabilities. RunLLM already does both.
- Results in days, not months. The RunLLM agent learns your stack quickly and efficiently – see your first RCA in days.
- Solves the unknown. 70%+ accuracy on novel incidents for one of the world's biggest B2B2C platforms.
- Never repeats mistakes. RunLLM learns from every single investigation, so it never makes the same mistake twice.
05 — The Team Behind RunLLM
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RunLLM was founded by PhDs and Professors from UC Berkeley's innovation center, RISELab, combining expertise in AI, LLMs, data systems, and scalable infrastructure.
FROM THE TEAM
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