RRepoGEO

REPOGEO REPORT · LITE

helixml/helix

Default branch main · commit 0c2e1355 · scanned 6/4/2026, 7:27:22 AM

GitHub: 778 stars · 75 forks

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 helixml/helix, 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
    Emphasize 'Private Agent Fleet with GPU-accelerated Desktop' in README intro

    Why:

    CURRENT
    **Deploy AI agents in your own data center or VPC and retain complete data security & control.** HelixML is an enterprise-grade platform for building and deploying AI agents with support for RAG (Retrieval-Augmented Generation), API calling, vision, and multi-provider LLM support.
    COPY-PASTE FIX
    **Deploy a private fleet of AI agents in your own data center or VPC, where each agent gets its own GPU-accelerated desktop, ensuring complete data security & control.** HelixML is an enterprise-grade platform for building and deploying these agents, supporting RAG, API calling, vision, and multi-provider LLMs.
  • mediumtopics#2
    Add specific topics to highlight private agent fleet and GPU desktops

    Why:

    CURRENT
    agents, api, genai, glm, golang, helm, k8s, kimi, llm, llm-agent, llm-serving, openai, openapi, qwen, rag, self-hosted, swagger, swarm
    COPY-PASTE FIX
    agents, api, genai, glm, golang, helm, k8s, kimi, llm, llm-agent, llm-serving, openai, openapi, qwen, rag, self-hosted, swagger, swarm, private-cloud, gpu-desktop, agent-orchestration, enterprise-ai
  • lowlicense#3
    Clarify the project's license(s) in the README

    Why:

    COPY-PASTE FIX
    Add a section or line in the README, e.g., '## License
This project is licensed under [specify license name(s) and terms, e.g., a custom license combining X and Y]. See the LICENSE file for full details.'

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 helixml/helix
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
LangChain
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. LangChain · recommended 1×
  2. Llama 2 · recommended 1×
  3. Mistral · recommended 1×
  4. Chroma · recommended 1×
  5. Weaviate · recommended 1×
  • CATEGORY QUERY
    How to deploy private AI agents with RAG and multi-provider LLM support on my infrastructure?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. Llama 2
    3. Mistral
    4. Chroma
    5. Weaviate
    6. Pinecone
    7. vLLM
    8. TGI (Text Generation Inference by Hugging Face)
    9. NVIDIA Triton Inference Server
    10. Qdrant
    11. FastAPI
    12. Flask
    13. Docker
    14. Kubernetes
    15. LlamaIndex
    16. Hugging Face Ecosystem
    17. Transformers
    18. Hugging Face Inference Endpoints
    19. sentence-transformers
    20. Elasticsearch
    21. Toolformer
    22. LocalAI
    23. Ollama
    24. Faiss
    25. Microsoft Azure AI Studio
    26. Azure Machine Learning
    27. Azure Machine Learning Endpoints
    28. Azure OpenAI Service
    29. Azure AI Search
    30. Azure Cognitive Search
    31. Azure Blob Storage
    32. Azure Data Lake Storage
    33. Prompt Flow
    34. Azure App Services
    35. AWS Bedrock
    36. Amazon SageMaker Endpoints
    37. Amazon OpenSearch Service
    38. Amazon Kendra
    39. Amazon S3
    40. EC2
    41. Agents for Amazon Bedrock

    AI recommended 41 alternatives but never named helixml/helix. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking a self-hosted platform for managing AI agents and LLMs with optimized GPU utilization.
    you: not recommended
    AI recommended (in order):
    1. Kubeflow (kubeflow/kubeflow)
    2. Run:ai
    3. MLflow (mlflow/mlflow)
    4. NVIDIA Triton Inference Server (triton-inference-server/server)
    5. OpenShift AI

    AI recommended 5 alternatives but never named helixml/helix. 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 helixml/helix?
    pass
    AI named helixml/helix explicitly

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

  • If a team adopts helixml/helix in production, what risks or prerequisites should they evaluate first?
    pass
    AI named helixml/helix 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 helixml/helix solve, and who is the primary audience?
    pass
    AI named helixml/helix 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 helixml/helix. 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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  • Deep reports10 / month
  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite
helixml/helix — RepoGEO report