Get AI alerts the moment your sensor data looks abnormal

Watches live sensor readings around the clock and emails your team the moment an AI flags something abnormal.

How the work actually flows

It branches. Exactly one path is taken; a person is alerted when a step fails.

Pattern: Exclusive Choice (4)

flowchart TD trig>"sensor reading streams in"]:::trig s0["check reading against patterns"]:::task s1["ai confirms real problem"]:::svc s2[("log confirmed issue")]:::store s3["email alert to team"]:::svc trig --> s0 s1 --> s2 s2 --> s3 gx{"× is reading unusual"}:::gate s0 --> gx p00["no action taken"]:::task gx -->|"normal reading"| p00 p10["ai reviews reading"]:::task gx -->|"unusual reading"| p10 p00 --> s1 p10 --> s1 out[/"team alerted to abnormal reading"/]:::out pay{{"catches problems before failures occur"}}:::pay s3 --> out out --> pay esc(("Alerts a person")):::human s2 -. "if it fails" .-> esc esc -.-> out 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 serviceA personA record or sheetOne path onlyResultPayoff
Build size
Advanced

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

Business functions
AI Agents & Autonomous SystemsEmail AutomationMessaging & NotificationsSpreadsheet & Database OpsReporting & AnalyticsEducation & Training
Connects
OpenAIPostgreSQL

The problem it solves

Keeping an eye on equipment or system readings around the clock isn't realistic for a small team, so problems often go unnoticed until something actually fails. By the time you catch an issue manually, it may already be costing you downtime or repairs.

Who it fits

Businesses with connected equipment, sensors, or systems who need to catch problems before they turn into costly failures.

How it works

  1. Sensor readings stream in continuously from your connected devices
  2. The system checks each reading against expected patterns
  3. AI reviews unusual readings to confirm whether they're a real problem
  4. Confirmed issues are logged for tracking
  5. An email alert is sent to your team with the details
What you get

Problems caught before equipment fails

Your connected sensors get watched around the clock, with an email alert the moment a reading looks abnormal enough to matter.

What you get

A real-time email alert describing the abnormal reading and where it came from.

What you need

Connected sensors or devices, a database, and an OpenAI or Anthropic 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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