Diagnose infrastructure alerts with AI and post findings to Mattermost

When an infrastructure alert fires, the system investigates automatically and posts a diagnosis to Mattermost before anyone is paged.

How the work actually flows

A straight line.

Pattern: Sequence (1)

flowchart TD trig>"infrastructure alert fires"]:::trig s0["filter duplicate alerts"]:::task s1["AI investigates alert"]:::svc s2["locate related chat thread"]:::task s3["post diagnostic report"]:::task trig --> s0 s0 --> s1 s1 --> s2 s2 --> s3 out[/"diagnostic report posted to thread"/]:::out pay{{"faster diagnosis before anyone paged"}}:::pay s3 --> out out --> pay classDef task fill:#e7f6fe,stroke:#34b8f0,color:#2c2a29 classDef svc fill:#f6f8fa,stroke:#7c8795,color:#2c2a29 classDef mi fill:#e7f6fe,stroke:#0079a8,color:#2c2a29,stroke-width:2px classDef human fill:#fff,stroke:#0079a8,color:#0079a8 classDef store fill:#f6f8fa,stroke:#0079a8,color:#2c2a29 classDef trig fill:#00a4eb,stroke:#0079a8,color:#fff,font-weight:bold classDef trigtime fill:#00a4eb,stroke:#0079a8,color:#fff,font-weight:bold classDef trigdata fill:#8ad4f5,stroke:#0079a8,color:#06314c,font-weight:bold classDef gate fill:#fff,stroke:#e8a23d,color:#6b4708,font-weight:bold classDef out fill:#1f9d6b,stroke:#167a53,color:#fff,font-weight:bold classDef pay fill:#06314c,stroke:#021f33,color:#fff
Starts itA stepAn outside serviceResultPayoff
Build size
Advanced

A larger build with multiple systems, AI reasoning, and custom rules.

Business functions
AI Agents & Autonomous SystemsKnowledge Base & RAGMessaging & NotificationsReporting & AnalyticsAPI & Webhook IntegrationDevOps & IT Operations
Connects
MattermostSlackOpenAIQdrant

The problem it solves

When something breaks at 3am, the on-call engineer wakes up to a wall of alerts and has to piece together what's actually wrong before they can fix it. Every minute spent diagnosing is a minute the issue keeps affecting customers.

Who it fits

IT operations and DevOps teams responsible for on-call incident response.

How it works

  1. An alert fires and comes in through Alertmanager
  2. Duplicate or repeated alerts are filtered out
  3. An AI agent investigates the alert, pulling extra context from connected systems
  4. The related conversation thread in Slack is located
  5. A diagnostic report with likely causes and recommendations is posted to the thread
What you get

Context your on-call engineer doesn't have to dig for

When an alert fires, your team gets a diagnosis with likely causes and next steps posted straight to Mattermost.

What you get

A diagnostic report posted alongside the alert, with likely causes and recommended next steps.

What you need

A Mattermost or Slack workspace, an OpenAI account, and access to your monitoring and infrastructure systems.

We can build this. But should you?

The hard question is not how to build it. It is whether this is the right thing to build first.

That is what a Fractional Chief AI Officer figures out with you, before anyone writes a line of code.

Let's Talk Strategy

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