RRepoGEO

REPOGEO REPORT · LITE

OpenMind/OM1

Default branch main · commit ba0935e7 · scanned 6/20/2026, 7:37:03 AM

GitHub: 2,842 stars · 994 forks

Scan history for this repo

Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.

Score trend (left → right: older → newer)

2 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

AI VISIBILITY SCORE
40 /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
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 OpenMind/OM1, 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 core identity

    Why:

    CURRENT
    OpenMind's OM1 is a modular AI runtime that empowers developers to create and deploy multimodal AI agents across digital environments and physical robots, including Humanoids, Phone Apps, Quadrupeds, educational robots such as TurtleBot 4, and simulators like Gazebo and Isaac Sim. OM1 agents can process diverse inputs like web data, social media, camera feeds, and LIDAR, while enabling physical actions including motion, autonomous navigation, and natural conversations. The goal of OM1 is to make it easy to create highly capable human-focused robots, that are easy to upgrade and (re)configure to accommodate different physical form factors.
    COPY-PASTE FIX
    OpenMind's OM1 is a modular AI runtime and Hardware Abstraction Layer (HAL) specifically designed for robotics. Unlike general-purpose AI assistants or local LLM applications, OM1 empowers developers to create and deploy multimodal AI agents across diverse physical robots (Humanoids, Quadrupeds, TurtleBot 4) and simulators (Gazebo, Isaac Sim), focusing on performance, modularity, and ease of integration for real-world robotic systems. OM1 agents can process diverse inputs like web data, social media, camera feeds, and LIDAR, while enabling physical actions including motion, autonomous navigation, and natural conversations. The goal of OM1 is to make it easy to create highly capable human-focused robots, that are easy to upgrade and (re)configure to accommodate different physical form factors.
  • mediumtopics#2
    Expand repository topics to include edge AI and hardware abstraction for robotics

    Why:

    CURRENT
    llm, multiagent, robotics, ros2, zenoh
    COPY-PASTE FIX
    llm, multiagent, robotics, ros2, zenoh, edge-ai, embedded-robotics, hardware-abstraction, robot-operating-system, inference-runtime
  • lowreadme#3
    Add a 'What OM1 is NOT' section to the README

    Why:

    COPY-PASTE FIX
    ## What OM1 is NOT
OM1 is not a general-purpose AI assistant application, a local LLM inference engine for desktop use, or a privacy-focused data processing tool. Its core mission is to provide a robust, modular Hardware Abstraction Layer (HAL) for deploying AI agents on physical and simulated robots.

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 OpenMind/OM1
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
ROS (Robot Operating System) / ROS 2
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. ROS (Robot Operating System) / ROS 2 · recommended 1×
  2. NVIDIA Isaac Sim · recommended 1×
  3. OpenAI Gym / Gymnasium · recommended 1×
  4. dm_control · recommended 1×
  5. PyBullet · recommended 1×
  • CATEGORY QUERY
    How to deploy multimodal AI agents on various physical robots and simulators?
    you: not recommended
    AI recommended (in order):
    1. ROS (Robot Operating System) / ROS 2
    2. NVIDIA Isaac Sim
    3. OpenAI Gym / Gymnasium
    4. dm_control
    5. PyBullet
    6. Gazebo
    7. Microsoft AirSim

    AI recommended 7 alternatives but never named OpenMind/OM1. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What AI runtime provides low-latency, efficient concurrency for edge robotics applications?
    you: not recommended
    AI recommended (in order):
    1. NVIDIA JetPack
    2. OpenVINO Toolkit
    3. ONNX Runtime
    4. TensorFlow Lite
    5. PyTorch Mobile

    AI recommended 5 alternatives but never named OpenMind/OM1. 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 OpenMind/OM1?
    pass
    AI named OpenMind/OM1 explicitly

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

  • If a team adopts OpenMind/OM1 in production, what risks or prerequisites should they evaluate first?
    pass
    AI named OpenMind/OM1 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 OpenMind/OM1 solve, and who is the primary audience?
    pass
    AI named OpenMind/OM1 explicitly

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

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OpenMind/OM1 — 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