RRepoGEO

REPOGEO REPORT · LITE

data-privacy-stack/presidio

Default branch main · commit 43c2452d · scanned 7/1/2026, 1:51:35 AM

GitHub: 9,784 stars · 1,176 forks

AI VISIBILITY SCORE
85 /100
Healthy
Category recall
2 / 2
Avg rank #3.5 when recommended
Rule findings
2 pass · 0 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 data-privacy-stack/presidio, 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

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

OVERALL DIRECTION
  • highreadme#1
    Reposition README's opening to clarify as an open-source framework for text, images, and structured data

    Why:

    CURRENT
    Context aware, pluggable and customizable PII de-identification service for text and images.
    COPY-PASTE FIX
    Presidio is an open-source framework (SDK) for context-aware, pluggable, and customizable PII de-identification across text, images, and structured data.
  • mediumtopics#2
    Add 'framework' to repository topics

    Why:

    COPY-PASTE FIX
    anonymization, data-anonymization, data-masking, data-obfuscation, data-privacy, data-redaction, de-identification, framework, guardrails, image-redactor, named-entity-recognition, nlp, personally-identifiable-information, phi, pii, pii-detection, privacy, python, sensitive-data, spacy, transformers
  • lowreadme#3
    Add a sentence about the primary audience to the README

    Why:

    COPY-PASTE FIX
    Presidio is designed for developers and data engineers building privacy-compliant applications that require robust PII detection and anonymization capabilities.

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
2 / 2
100% of queries surface data-privacy-stack/presidio
Avg rank
#3.5
Lower is better. #1 = top recommendation.
Share of voice
12%
Of all named tools, what % are you?
Top rival
Microsoft Azure Purview
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Microsoft Azure Purview · recommended 1×
  2. Microsoft Azure Information Protection (AIP) · recommended 1×
  3. Google Cloud Data Loss Prevention (DLP) API · recommended 1×
  4. Amazon Macie · recommended 1×
  5. Amazon Comprehend Medical · recommended 1×
  • CATEGORY QUERY
    How to automatically detect and anonymize PII in text, images, and structured data?
    you: #6
    AI recommended (in order):
    1. Microsoft Azure Purview
    2. Microsoft Azure Information Protection (AIP)
    3. Google Cloud Data Loss Prevention (DLP) API
    4. Amazon Macie
    5. Amazon Comprehend Medical
    6. Presidio (microsoft/presidio) ← you
    7. NLTK (nltk/nltk)
    8. spaCy (explosion/spaCy)
    9. Privitar Data Privacy Platform
    10. Immuta
    11. DataGrail
    12. OneTrust DataDiscovery & Classification
    Show full AI answer
  • CATEGORY QUERY
    Looking for a Python library to redact sensitive information using NLP and customizable pipelines.
    you: #1
    AI recommended (in order):
    1. Presidio ← you
    2. Faker
    3. spaCy
    4. NLTK
    5. Pii-Tools
    Show full AI answer

Objective checks

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

  • Metadata completeness
    pass

  • 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 data-privacy-stack/presidio?
    pass
    AI named data-privacy-stack/presidio explicitly

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

  • If a team adopts data-privacy-stack/presidio in production, what risks or prerequisites should they evaluate first?
    pass
    AI named data-privacy-stack/presidio 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 data-privacy-stack/presidio solve, and who is the primary audience?
    pass
    AI named data-privacy-stack/presidio explicitly

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

Embed your GEO score

Drop this badge into the README of data-privacy-stack/presidio. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

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data-privacy-stack/presidio — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

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  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite