RRepoGEO

REPOGEO REPORT · LITE

orailnoor/cross-platform-llm-client

Default branch main · commit 9bfd923e · scanned 6/13/2026, 12:31:48 AM

GitHub: 527 stars · 114 forks

AI VISIBILITY SCORE
28 /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
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 orailnoor/cross-platform-llm-client, 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
  • highreadme#1
    Reposition the README's opening sentence to emphasize 'application'

    Why:

    CURRENT
    A production-ready, cross-platform AI chat client built with Flutter. It unifies local on-device LLM inference (Android) with cloud API access, giving users full control over how their models run.
    COPY-PASTE FIX
    PrivateLM is a production-ready, cross-platform **AI chat application** built with Flutter. It serves as a unified **end-user client** for local on-device LLM inference (Android) and cloud API access, giving users full control over how their models run.
  • mediumhomepage#2
    Add the project's homepage URL to the repository metadata

    Why:

    COPY-PASTE FIX
    https://ai-chat-orailnoor.web.app/

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 orailnoor/cross-platform-llm-client
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
microsoft/onnxruntime
Recommended in 4 of 2 queries
COMPETITOR LEADERBOARD
  1. microsoft/onnxruntime · recommended 4×
  2. huggingface/transformers.js · recommended 2×
  3. ggerganov/llama.cpp · recommended 2×
  4. Flutter · recommended 1×
  5. TensorFlow Lite · recommended 1×
  • CATEGORY QUERY
    How to build a mobile app with on-device AI inference and cloud API fallback?
    you: not recommended
    AI recommended (in order):
    1. Flutter
    2. TensorFlow Lite
    3. Firebase ML Kit
    4. React Native
    5. TensorFlow.js
    6. Google Cloud AI Platform
    7. AWS SageMaker
    8. Azure Machine Learning
    9. Swift
    10. Objective-C
    11. Core ML
    12. CloudKit
    13. Kotlin
    14. Java
    15. Xamarin
    16. ML.NET

    AI recommended 16 alternatives but never named orailnoor/cross-platform-llm-client. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Cross-platform framework for a private, multimodal AI chat client with local model support?
    you: not recommended
    AI recommended (in order):
    1. Electron (electron/electron)
    2. Transformers.js (huggingface/transformers.js)
    3. ONNX Runtime Web (microsoft/onnxruntime)
    4. Flutter (flutter/flutter)
    5. llama.cpp (ggerganov/llama.cpp)
    6. ONNX Runtime Mobile (microsoft/onnxruntime)
    7. Tauri (tauri-apps/tauri)
    8. Transformers.js (huggingface/transformers.js)
    9. llama.cpp (ggerganov/llama.cpp)
    10. Qt (qt/qt)
    11. ONNX Runtime C++ API (microsoft/onnxruntime)
    12. PyTorch C++ API (LibTorch) (pytorch/pytorch)
    13. GGML (ggerganov/ggml)
    14. Avalonia UI (AvaloniaUI/Avalonia)
    15. ML.NET (dotnet/machinelearning)
    16. ONNX Runtime C# API (microsoft/onnxruntime)

    AI recommended 16 alternatives but never named orailnoor/cross-platform-llm-client. 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 orailnoor/cross-platform-llm-client?
    pass
    AI named orailnoor/cross-platform-llm-client explicitly

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

  • If a team adopts orailnoor/cross-platform-llm-client in production, what risks or prerequisites should they evaluate first?
    pass
    AI named orailnoor/cross-platform-llm-client 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 orailnoor/cross-platform-llm-client solve, and who is the primary audience?
    pass
    AI did not name orailnoor/cross-platform-llm-client — 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?

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orailnoor/cross-platform-llm-client — 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