RRepoGEO

REPOGEO REPORT · LITE

eyelevelai/groundx-on-prem

Default branch main · commit 6c7c33e2 · scanned 6/10/2026, 7:27:22 PM

GitHub: 815 stars · 89 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
22 /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
1 / 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 eyelevelai/groundx-on-prem, 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 to highlight on-prem RAG and Kubernetes

    Why:

    CURRENT
    # GroundX On-Prem/On-Cloud Kubernetes Infrastructure As Code

## Table of Contents

**[What is GroundX On-Prem?](#what-is-groundx-on-prem)[GroundX Ingest Service](#groundx-ingest-service)
    COPY-PASTE FIX
    # GroundX On-Prem/On-Cloud Kubernetes Infrastructure As Code

GroundX On-Prem provides a self-hosted, Kubernetes-native infrastructure-as-code solution for deploying the GroundX enterprise RAG (Retrieval Augmented Generation) platform. It enables organizations to build AI applications with their private data, ensuring complete data sovereignty, security, and compliance by running document parsing, storage, and semantic search capabilities within their own private cloud or on-premise environments.

## Table of Contents

**[What is GroundX On-Prem?](#what-is-groundx-on-prem)[GroundX Ingest Service](#groundx-ingest-service)
  • mediumreadme#2
    Clarify the existing license in the README

    Why:

    COPY-PASTE FIX
    This project is licensed under the terms found in the [LICENSE](LICENSE) file. Please refer to the LICENSE file for specific details regarding usage, distribution, and modification.

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 eyelevelai/groundx-on-prem
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Elasticsearch
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Elasticsearch · recommended 2×
  2. OpenSearch · recommended 2×
  3. Milvus · recommended 2×
  4. PostgreSQL · recommended 2×
  5. ECK (Elastic Cloud on Kubernetes) · recommended 1×
  • CATEGORY QUERY
    Looking for a Kubernetes-native solution for document ingestion, storage, and semantic search.
    you: not recommended
    AI recommended (in order):
    1. Elasticsearch
    2. ECK (Elastic Cloud on Kubernetes)
    3. OpenSearch
    4. OpenSearch Operator
    5. Qdrant
    6. Qdrant Kubernetes Operator
    7. Weaviate
    8. Weaviate Kubernetes Operator
    9. Milvus
    10. Milvus Operator
    11. PostgreSQL
    12. pgvector

    AI recommended 12 alternatives but never named eyelevelai/groundx-on-prem. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    How to deploy a private cloud document parsing and search service on Kubernetes infrastructure?
    you: not recommended
    AI recommended (in order):
    1. Elastic Stack
    2. Elasticsearch
    3. Kibana
    4. Beats
    5. Logstash
    6. Apache Solr
    7. MinIO
    8. Apache Tika
    9. PostgreSQL
    10. pg_search
    11. pg_trgm
    12. Meilisearch
    13. OpenSearch
    14. OpenSearch Dashboards
    15. Milvus
    16. Hugging Face Transformers
    17. sentence-transformers

    AI recommended 17 alternatives but never named eyelevelai/groundx-on-prem. 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 eyelevelai/groundx-on-prem?
    pass
    AI did not name eyelevelai/groundx-on-prem — 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?

  • If a team adopts eyelevelai/groundx-on-prem in production, what risks or prerequisites should they evaluate first?
    pass
    AI named eyelevelai/groundx-on-prem 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 eyelevelai/groundx-on-prem solve, and who is the primary audience?
    pass
    AI did not name eyelevelai/groundx-on-prem — 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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eyelevelai/groundx-on-prem — 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