RRepoGEO

REPOGEO REPORT · LITE

atiilla/GeoIntel

Default branch main · commit c65f52aa · scanned 5/25/2026, 5:53:16 AM

GitHub: 1,049 stars · 149 forks

AI VISIBILITY SCORE
33 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
2 pass · 0 warn · 0 fail
Objective metadata checks
AI knows your name
2 / 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 atiilla/GeoIntel, 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 the README's opening paragraph to clarify its specialized niche

    Why:

    CURRENT
    # GeoIntel

Python tool using Google's Gemini API to uncover the location where photos were taken through AI-powered geo-location analysis.
    COPY-PASTE FIX
    # GeoIntel

GeoIntel is a specialized Python tool and web interface for AI-powered geo-location analysis, designed to uncover the precise location where photos were taken. Leveraging Google's Gemini API, it provides a powerful solution for OSINT investigations, digital forensics, and geospatial intelligence.
  • highabout#2
    Refine the repository's 'About' description for clarity and specificity

    Why:

    CURRENT
    GeoIntel using Google's Gemini API to uncover the location where photos were taken through AI-powered geo-location analysis.
    COPY-PASTE FIX
    GeoIntel: AI-powered Python tool and web interface for precise photo geolocation, ideal for OSINT, digital forensics, and geospatial intelligence using Google's Gemini API.
  • mediumreadme#3
    Add a 'Comparison to Alternatives' section in the README

    Why:

    COPY-PASTE FIX
    ## Comparison to Alternatives

Unlike general image search engines (e.g., Google Lens, Yandex Image Search) or broad computer vision libraries (e.g., OpenCV, TensorFlow, Google Cloud Vision AI), GeoIntel is specifically engineered for precise AI-driven geolocation analysis of photographs. It focuses on providing actionable intelligence for OSINT and forensic investigations, offering both a command-line interface and an interactive web tool for dedicated analysis.

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 atiilla/GeoIntel
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Google Lens
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Google Lens · recommended 1×
  2. Picarta.ai · recommended 1×
  3. GeoGuessr · recommended 1×
  4. Yandex Image Search · recommended 1×
  5. Microsoft Bing Visual Search · recommended 1×
  • CATEGORY QUERY
    What tool uses AI to pinpoint the exact location where a photograph was captured?
    you: not recommended
    AI recommended (in order):
    1. Google Lens
    2. Picarta.ai
    3. GeoGuessr
    4. Yandex Image Search
    5. Microsoft Bing Visual Search
    6. ExifTool
    7. Jeffrey's Exif Viewer

    AI recommended 7 alternatives but never named atiilla/GeoIntel. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Need a Python library or web tool for AI-driven geolocation analysis of images.
    you: not recommended
    AI recommended (in order):
    1. Picarta
    2. Google Cloud Vision AI
    3. Microsoft Azure Computer Vision
    4. OpenCV
    5. TensorFlow
    6. PyTorch
    7. Geolocate.ai
    8. What3words

    AI recommended 8 alternatives but never named atiilla/GeoIntel. This is the gap to close.

    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 atiilla/GeoIntel?
    pass
    AI did not name atiilla/GeoIntel — likely talking about a different project

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

  • If a team adopts atiilla/GeoIntel in production, what risks or prerequisites should they evaluate first?
    pass
    AI named atiilla/GeoIntel 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 atiilla/GeoIntel solve, and who is the primary audience?
    pass
    AI named atiilla/GeoIntel 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 atiilla/GeoIntel. 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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MARKDOWN (README)
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atiilla/GeoIntel — 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