Flag suspicious product reviews before they mislead customers

The system scans new product reviews with AI and alerts your team in Slack when one looks fake.

How the work actually flows

It branches. Exactly one path is taken; runs once per each new review.

Pattern: Exclusive Choice (4) · Multiple Instances with a priori Design-Time Knowledge (13)

flowchart TD trig(["runs on a schedule"]):::trigtime s0[["check for duplicate reviews"]]:::mi s1["ai scores fake likelihood"]:::task s2[("save score to airtable")]:::store trig --> s0 s0 --> s1 s1 --> s2 gx{"× is the review high risk"}:::gate s2 --> gx p00["alert moderation team in slack"]:::task gx -->|"high risk"| p00 p10["no alert sent"]:::task gx -->|"low risk"| p10 p00 --> out p10 --> out out[/"scored review log with risk alerts"/]:::out pay{{"catch fake reviews before customers see them"}}:::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 itemA record or sheetOne path onlyResultPayoff
Build size
Advanced

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

Business functions
Messaging & NotificationsSpreadsheet & Database Ops
Connects
AirtableOpenAISlack
Featured in

The problem it solves

Fake reviews can slip past you and quietly damage trust in your product or marketplace. Manually reading through every review to spot manipulation is not realistic once volume grows.

Who it fits

E-commerce marketplaces and sellers who rely on customer reviews.

How it works

  1. New reviews for a product are pulled in automatically
  2. Each review is checked against previous ones to avoid duplicates
  3. AI analyzes the review and scores how likely it is to be fake
  4. The result is saved to Airtable for your records
  5. Reviews above your risk threshold trigger a Slack alert to your moderation team
What you get

Fake reviews caught before they mislead a shopper

Suspicious reviews get flagged to your team so you can catch fakes before they influence a customer's purchase decision.

What you get

A scored review log in Airtable and instant Slack alerts on high-risk reviews.

What you need

An Airtable account, an OpenAI account, and a Slack workspace.

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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