RRepoGEO

REPOGEO REPORT · LITE

microsoft/Foundry-Local

Default branch main · commit 2087b312 · scanned 5/26/2026, 7:01:28 PM

GitHub: 2,303 stars · 311 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 microsoft/Foundry-Local, 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
  • highabout#1
    Add a concise description to the repository's About section

    Why:

    COPY-PASTE FIX
    An end-to-end local AI solution providing native SDKs, optimized models, and automatic hardware acceleration for building applications that run entirely on the user's device, ensuring privacy and offline functionality.
  • highreadme#2
    Reposition the README's main heading to clarify its category

    Why:

    CURRENT
    <h1>Foundry Local</h1>
    COPY-PASTE FIX
    <h1>Foundry Local: End-to-End Solution for On-Device AI Applications</h1>
  • mediumreadme#3
    Clarify the existing license in the README

    Why:

    COPY-PASTE FIX
    ## License
This project uses a custom license. Please refer to the [LICENSE file](LICENSE) for full details regarding usage and distribution.

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 microsoft/Foundry-Local
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
TensorFlow Lite
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. TensorFlow Lite · recommended 2×
  2. Core ML · recommended 2×
  3. ONNX Runtime · recommended 2×
  4. PyTorch Mobile · recommended 1×
  5. ML.NET · recommended 1×
  • CATEGORY QUERY
    How to integrate AI models directly into applications for on-device inference and privacy?
    you: not recommended
    AI recommended (in order):
    1. TensorFlow Lite
    2. Core ML
    3. ONNX Runtime
    4. PyTorch Mobile
    5. ML.NET
    6. MediaPipe

    AI recommended 6 alternatives but never named microsoft/Foundry-Local. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What SDKs enable fast, offline speech-to-text and chat completions on user devices?
    you: not recommended
    AI recommended (in order):
    1. Apple Speech Framework
    2. Core ML
    3. Mozilla DeepSpeech
    4. ONNX Runtime
    5. Llama 2
    6. Mistral
    7. Phi-2
    8. Picovoice Rhino Speech-to-Intent
    9. Picovoice Leopard Speech-to-Text
    10. Google ML Kit
    11. TensorFlow Lite
    12. Gemma
    13. Coqui STT
    14. Vosk
    15. Kaldi
    16. OpenAI Whisper.cpp
    17. Llama.cpp

    AI recommended 17 alternatives but never named microsoft/Foundry-Local. 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 microsoft/Foundry-Local?
    pass
    AI named microsoft/Foundry-Local explicitly

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

  • If a team adopts microsoft/Foundry-Local in production, what risks or prerequisites should they evaluate first?
    pass
    AI named microsoft/Foundry-Local 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 microsoft/Foundry-Local solve, and who is the primary audience?
    pass
    AI named microsoft/Foundry-Local 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 microsoft/Foundry-Local. 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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HTML
<a href="https://repogeo.com/en/r/microsoft/Foundry-Local"><img src="https://repogeo.com/badge/microsoft/Foundry-Local.svg" alt="RepoGEO" /></a>
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microsoft/Foundry-Local — 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