Catch equipment sensor anomalies before they become problems

Watches your sensor readings around the clock, uses AI to spot anomalies, and alerts your team by Slack or email.

How the work actually flows

It branches. Every path runs; runs once per each sensor reading.

Pattern: Parallel Split (2)

flowchart TD trig>"new sensor reading arrives"]:::trig s0[["filter duplicate readings"]]:::mi s1["ai checks against safety thresholds"]:::task trig --> s0 s0 --> s1 gx{"+ what happens to reading"}:::gate s1 --> gx p00["route to slack or email"]:::task gx -->|"alert if anomaly found"| p00 p10["record reading and analysis"]:::task gx -->|"log reading always"| p10 p00 --> out p10 --> out out[/"anomaly alerts and full reading log"/]:::out pay{{"catches equipment issues before failure"}}:::pay 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 stepRuns once per itemEvery pathResultPayoff
Build size
Advanced

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

Business functions
AI Agents & Autonomous SystemsEmail AutomationMessaging & NotificationsSpreadsheet & Database Ops
Connects
Google SheetsGmailSlackOpenAI

The problem it solves

You're relying on someone to notice a sensor reading looks off before it turns into equipment damage or downtime. With data streaming in constantly, it's easy for a slow drift or a sudden spike to go unnoticed until it's already a problem.

Who it fits

A facilities, manufacturing, or operations team monitoring IoT sensors for equipment health.

How it works

  1. Sensor readings stream in continuously, or are pulled in on a schedule.
  2. Duplicate readings are filtered out so the same data isn't processed twice.
  3. AI compares each reading against your defined safety thresholds to spot anomalies.
  4. Depending on severity, an alert goes to Slack or email.
  5. Every reading and analysis is logged into Google Sheets for a full history.
What you get

Equipment failures caught before they happen

You get round-the-clock monitoring of your equipment sensors with an instant Slack or email alert the moment something looks wrong.

What you get

Real-time anomaly alerts and a running log of sensor readings and analysis.

What you need

A Google Workspace account, an OpenAI API key, and a Slack or email account.

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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