RRepoGEO

REPOGEO REPORT · LITE

langflow-ai/openrag

Default branch main · commit 35845856 · scanned 6/19/2026, 5:56:14 AM

GitHub: 4,214 stars · 428 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
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 langflow-ai/openrag, 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
    Clarify README's opening statement to emphasize 'platform' and 'end-to-end solution'

    Why:

    CURRENT
    OpenRAG is a comprehensive Retrieval-Augmented Generation platform that enables intelligent document search and AI-powered conversations.
    COPY-PASTE FIX
    OpenRAG is a comprehensive, all-in-one Retrieval-Augmented Generation (RAG) platform for building intelligent agent-powered document search and chat systems, especially for enterprise data.
  • mediumabout#2
    Expand the 'About' description with key features and use cases

    Why:

    CURRENT
    OpenRAG is a comprehensive, single package Retrieval-Augmented Generation platform built on Langflow, Docling, and Opensearch.
    COPY-PASTE FIX
    OpenRAG is a comprehensive, single-package Retrieval-Augmented Generation (RAG) platform for building AI-powered document search and chat systems. It supports agentic RAG workflows for enterprise documents, built on Langflow, Docling, and Opensearch.

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 langflow-ai/openrag
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Pinecone
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Pinecone · recommended 2×
  2. LangChain · recommended 2×
  3. LlamaIndex · recommended 2×
  4. Haystack · recommended 2×
  5. OpenAI · recommended 1×
  • CATEGORY QUERY
    How to build an AI-powered document search and chat system for my data?
    you: not recommended
    AI recommended (in order):
    1. Pinecone
    2. OpenAI
    3. LangChain
    4. Weaviate
    5. Cohere
    6. LlamaIndex
    7. Qdrant
    8. Hugging Face Transformers
    9. Haystack
    10. Elasticsearch
    11. Chroma

    AI recommended 11 alternatives but never named langflow-ai/openrag. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for an all-in-one platform to implement agentic RAG for enterprise documents.
    you: not recommended
    AI recommended (in order):
    1. LlamaIndex
    2. LangChain
    3. LangServe
    4. LangSmith
    5. Haystack
    6. Azure AI Search
    7. Azure OpenAI Service
    8. Amazon Kendra
    9. Amazon Bedrock
    10. Cohere Coral
    11. Pinecone

    AI recommended 11 alternatives but never named langflow-ai/openrag. 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 langflow-ai/openrag?
    pass
    AI named langflow-ai/openrag explicitly

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

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

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

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langflow-ai/openrag — 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