Unprofane

Unprofane vs Azure AI Content Safety

Profanity scored on its own, every disguise named, and a free key in a minute.

Unprofane’s accuracy, published
Toxic text caught
89.0%
Clean text flagged
7.0%
Innocent words flagged
0.0%

Azure AI Content Safety: not run on our benchmark, so no figure for it here.

Head to head, 2026-09-28; the Scunthorpe Test, 2026-10-20. How it was measured

Why Unprofane over Azure AI Content Safety

Side by side

Each line on Azure AI Content Safety cites its own pages, one click away.

QuestionUnprofaneAzure AI Content Safety
Accuracy, published

89.0% of toxic text caught at 7.0% clean flagged, on a private test set; 0.0% of the Scunthorpe Test’s innocent words flagged. See it

Not run on our benchmark: no figure here.

What it moderates

Profanity, slurs, insults, threats, sexual language, self-harm and reserved names, in 17 languages, with 17 disguises undone and named. Text only. See it

Text scored for hate, sexual content, violence and self-harm. [1]

Swearing aimed at no group is a low level of hate. [2]

What an answer shows

The decision and why: each word, where it was, how it was disguised, its severity, a censored version and the engine version. See it

A severity for each category, and any blocklist items it matched. [3]

Severity on a scale of 0 to 7, or four steps of it. [2]

Deployment and upkeep

Nothing to install or run: one HTTPS call, answered at Cloudflare’s edge. Engine versions are dated and never change once published. See it

An Azure subscription, and a resource in a supported region. [1]

Review by people

Allow, review or block, set by audience (kids, teen, standard, strict), so only what needs a person reaches your team. See it

A Studio to set up a moderation workflow and watch it. [1]

Integrations

JavaScript and Python SDKs, an MCP server, a Perspective-compatible endpoint, and recipes for Supabase, Clerk, Firebase, Auth0, Better Auth, Unity and Godot. See it

A REST API, client libraries and the Studio. [4]

Pricing

From $9 a month for 25,000 checks, with a published overage rate. Free test keys, 100 checks a day, no card. See it

A free tier and a paid one, F0 and S0. [1]

Processing and retention

Kept 90 days when the model reads it, then deleted; Growth, Scale and Enterprise can turn that off. Never logged or cached. See it

Inputs not stored or used for training; blocklists are kept. [4]

Shown in the engine’s own answers

  1. Try to fool it

    The live engine. Type a disguised word and watch it read; type an innocent one and watch it pass.

    Enter to check

  2. Measured in public

    False positives on innocent words are counted and published, and run again for every engine version.

    0.0%

    false positives on 1,470 innocent words and phrases, the Scunthorpe Test of 2026-10-20

    • Scunthorpeallow
    • Dickinsonallow
    • cockatooallow
    • Sussexallow
    • shiitakeallow
    • breast cancer screeningallow

Make the first call

One request in the language you use. The answer carries the evidence.

curl -X POST https://api.unprofane.com/v1/check \
  -H "Authorization: Bearer up_test_YOUR_KEY" \
  -H "Content-Type: application/json" \
  -d '{"text":"xXsh1tXx","context":"username","policy":"teen"}'
Sources on Azure AI Content Safety: its own pages, read October 13, 2026
  1. [1]Microsoft, What is Azure AI Content Safety?. Read .
  2. [2]Microsoft, Harm categories in Azure AI Content Safety. Read .
  3. [3]Microsoft, Text Operations: Analyze Text (REST API). Read .
  4. [4]Microsoft, Data, privacy, and security for AI Content Safety. Read .

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