Aqweth sees your production so your engineers don't have to.
Agentic AI for autonomous root-cause analysis. 15 parallel fetch nodes investigate across logs, metrics, traces, deploys, and code — and report back in plain language within seconds.
Root cause
Null check removed in PaymentProcessor.validate() in commit a3f92b (deploy 14:28).
Suggested fix
Revert to v2.4.0 or patch null guard on line 142.
Production incidents cost more than downtime.
Two structural problems compound every incident.
problem · 01
Access walls
Engineers are paged at 3 AM and spend the first 20 minutes navigating VPN, requesting elevated access, and waiting for approval. By the time they reach logs, the critical window has passed.
problem · 02
Tool fragmentation
RCA means manually cross-referencing five different systems with no shared timeline. Every tool has a different auth flow, a different query syntax, and a different data model — all under pressure, in the middle of the night.
One investigation. Fifteen sources. Seconds.
Triage runs first — noise dismissed before a single LLM token is spent.
/rca · alert · proactive
Trigger
Invoke with /rca in Slack, connect to your alerting pipeline, or let Aqweth run proactive scans on schedule. Any alert format, any channel.
Dedupe + classify
Triage
Signal is separated from noise before a single LLM token is spent. Duplicate alerts are merged, severity is classified, irrelevant signals are dropped.
15 fetch nodes · parallel
Fan-out
Up to 15 fetch nodes execute in parallel, each querying a different backend. Slow or offline backends time out gracefully — the rest continue.
RCA card → chat
Synthesise
All evidence is assembled into a structured RCA card with confidence score, root cause, and suggested fix. Streamed directly to the Slack thread that triggered the investigation.
Aqweth recommends. Your engineers act.
The only production action Aqweth can take is opening a Jira ticket — and only on explicit approval.
No automation, no surprises, no "AI rolled back the deploy while you slept."
RCA card posted
in Slack / Chat
Engineer reviews
evidence, confidence, fix
Approve or reject
human_review interrupt
on approve only ↓
Jira ticket opened
with full RCA evidence attached
Fits the stack you already have.
Switching backends is one line in aqweth.yaml.
No code. No rebuild.
Data residency on your terms.
Run all inference in your cluster. Or use cloud APIs. Or mix both. One config file either way.
Cloud API
Self-hosted
Mix both: embedder + triage self-hosted, reasoning via cloud API. One YAML line per role.
Always on. Not just when alerts fire.
Aqweth catches degradation before it crosses thresholds.
Anomaly scan
z-score + EWMA on error rates and latency per service.
Correlation sweep
Multi-service degradation within a time window.
Health digest
Deterministic summary posted to SRE channel.
Trend report
Week-on-week regressions, no LLM cost.
Nightly embed
Resolved incidents + runbooks → vector store.
Let us run an investigation on one of your incidents.
No deployment required. You nominate an incident from your retro doc — we run the analysis together.
Request accessOr email us at hello@aqweth.ai · No commitment