Analyze company reviews for workplace bias patterns with AI

Pulls public company reviews, uses AI to spot demographic rating gaps, and charts the results automatically.

How the work actually flows

A straight line.

Pattern: Sequence (1)

flowchart TD trig(("company name provided")):::human s0["collect review data"]:::svc s1["extract demographic ratings"]:::task s2["calculate statistical differences"]:::task s3["generate charts"]:::task trig --> s0 s0 --> s1 s1 --> s2 s2 --> s3 out[/"bias pattern report generated"/]:::out pay{{"data-backed equity insights"}}:::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
A stepAn outside serviceA personResultPayoff
Build size
Advanced

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

Business functions
Web Scraping & Data Collection
Connects
OpenAI

The problem it solves

You suspect there may be patterns worth investigating in how different groups rate a workplace, but manually reading through hundreds of reviews and doing the statistics yourself is not realistic. Without the data laid out clearly, it is hard to know if a concern is real or anecdotal.

Who it fits

HR teams, researchers, or advocacy groups investigating workplace equity at a specific company.

How it works

  1. You provide the name of the company you want to analyze
  2. The automation collects public review data for that company
  3. AI reads the reviews and extracts demographic-based ratings
  4. Statistical measures are calculated to flag meaningful differences
  5. Charts are generated to visualize any patterns found
What you get

Bias patterns you can see before you act

You get a data-backed view of demographic rating gaps in a company's public reviews.

What you get

A set of visual reports and statistics showing rating differences across demographic groups.

What you need

A web scraping service account and an OpenAI API key.

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

Related automations

Publish AI-written news articles to WordPress from trends

The system spots trending topics, researches them, writes an article, and publishes it to your WordPress site.

Advanced

Turn competitor blog posts into a fresh draft with a matching image

It reads other companies' blog posts, rewrites them, and saves a finished draft with an image to Google Drive.

Advanced

Turn Reddit questions into content ideas in a Google Sheet

Scans chosen subreddits for real questions people are asking and turns them into ready-to-use content ideas in a spreadsheet.

Advanced

Turn curated articles into a translated, ready-to-send newsletter

The system translates each article, formats it in HTML, and assembles a finished newsletter ready to send.

Advanced
Back to the AI Playbook