RRepoGEO

REPOGEO REPORT · LITE

openai/privacy-filter

Default branch main · commit f7f00ca7 · scanned 5/10/2026, 11:52:16 PM

GitHub: 2,062 stars · 179 forks

AI VISIBILITY SCORE
35 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 1 warn · 0 fail
Objective metadata checks
AI knows your name
3 / 3
Direct prompts that named your repo
HOW TO READ THIS REPORT

Action plan is what to do next — copy-pasteable changes prioritized by impact. Category visibility is the real GEO test: when a user asks an AI a brand-free question that should surface openai/privacy-filter, does the AI actually recommend you — or your competitors? Objective checks verify the metadata signals AI engines weight first. Self-mention check detects whether AI even knows you exist by name.

Action plan — copy-paste fixes

2 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • mediumreadme#1
    Emphasize key differentiators in the README's opening sentence

    Why:

    CURRENT
    OpenAI Privacy Filter is a bidirectional token-classification model for personally identifiable information (PII) detection and masking in text. It is intended for high-throughput data sanitization workflows where teams need a model that they can run on-premises that is fast, context-aware, and tunable.
    COPY-PASTE FIX
    OpenAI Privacy Filter is a fast, on-premises, and highly tunable bidirectional token-classification model for personally identifiable information (PII) detection and masking in text, designed for high-throughput data sanitization workflows.
  • mediumhomepage#2
    Add a homepage URL to the repository

    Why:

    COPY-PASTE FIX
    https://github.com/openai/privacy-filter

Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash

Category visibility — the real GEO test

Brand-free queries asked to google/gemini-2.5-flash. Did AI recommend you, or someone else?

Same questions for every model — switch tabs to compare answers and rankings.

Recall
0 / 2
0% of queries surface openai/privacy-filter
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
microsoft/presidio
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. microsoft/presidio · recommended 2×
  2. Google Cloud Data Loss Prevention (DLP) API · recommended 2×
  3. Amazon Macie · recommended 1×
  4. Private AI · recommended 1×
  5. NIST/NIST-PII-Scrubber · recommended 1×
  • CATEGORY QUERY
    How can I detect and mask personally identifiable information in text data efficiently?
    you: not recommended
    AI recommended (in order):
    1. Presidio (microsoft/presidio)
    2. Google Cloud Data Loss Prevention (DLP) API
    3. Amazon Macie
    4. Private AI
    5. NIST PII Scrubber (NIST/NIST-PII-Scrubber)
    6. spaCy (explosion/spaCy)
    7. Regex (Regular Expressions)

    AI recommended 7 alternatives but never named openai/privacy-filter. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are fast, on-premises tools for redacting PII from large text datasets?
    you: not recommended
    AI recommended (in order):
    1. Presidio (microsoft/presidio)
    2. Google Cloud Data Loss Prevention (DLP) API
    3. Privitar Data Privacy Platform
    4. IBM Watson Knowledge Catalog
    5. NIST PII Redaction Toolkit
    6. HPE SecureData

    AI recommended 6 alternatives but never named openai/privacy-filter. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    warn

    Suggestion:

  • README presence
    pass

Self-mention check

Does AI even know your repo exists when asked about it directly?

  • Compared to common alternatives in this category, what is the core differentiator of openai/privacy-filter?
    pass
    AI named openai/privacy-filter explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • If a team adopts openai/privacy-filter in production, what risks or prerequisites should they evaluate first?
    pass
    AI named openai/privacy-filter explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • In one sentence, what problem does the repo openai/privacy-filter solve, and who is the primary audience?
    pass
    AI named openai/privacy-filter explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

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openai/privacy-filter — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

  • Deep reports10 / month
  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite