REPOGEO REPORT · LITE

run-llama/llama_cloud_services

Default branch main · commit f385e96a · scanned 5/9/2026, 10:12:21 PM

GitHub: 4,250 stars · 473 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 run-llama/llama_cloud_services, 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

Add a clear, concise description of the service's purpose to the README

Why:

CURRENT

# Llama Cloud Services

> ⚠️ DEPRECATION NOTICE

COPY-PASTE FIX

# Llama Cloud Services

Llama Cloud Services provided a fully managed, cloud-hosted platform designed for developers and businesses to build and deploy LlamaIndex-powered RAG applications, specializing in knowledge agents and document management. It offered robust tools for structured data extraction and processing from various document types.

> ⚠️ DEPRECATION NOTICE

mediumtopics#2

Expand topics to include cloud, RAG, and knowledge management terms

Why:

CURRENT

document, document-parser, document-parsing, docx-to-markdown, parsing, pdf, pdf-document-processor, pdf-to-excel, pdf-to-json, pdf-to-markdown, pdf-to-text, ppt-to-json, ppt-to-markdown, pptx, structured-data, tables

COPY-PASTE FIX

document, document-parser, document-parsing, docx-to-markdown, parsing, pdf, pdf-document-processor, pdf-to-excel, pdf-to-json, pdf-to-markdown, pdf-to-text, ppt-to-json, ppt-to-markdown, pptx, structured-data, tables, cloud-service, knowledge-management, rag, llamaindex, ai-applications

lowtopics#3

Remove overly granular document parsing topics

Why:

CURRENT

document, document-parser, document-parsing, docx-to-markdown, parsing, pdf, pdf-document-processor, pdf-to-excel, pdf-to-json, pdf-to-markdown, pdf-to-text, ppt-to-json, ppt-to-markdown, pptx, structured-data, tables

COPY-PASTE FIX

document, document-parser, document-parsing, docx-to-markdown, parsing, pdf, pdf-document-processor, pdf-to-markdown, pdf-to-text, ppt-to-markdown, pptx, structured-data, tables

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 run-llama/llama_cloud_services

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

Google Cloud Document AI

Recommended in 2 of 2 queries

COMPETITOR LEADERBOARD

Google Cloud Document AI · recommended 2×
Apache Tika · recommended 1×
Microsoft Azure Form Recognizer / Document Intelligence · recommended 1×
Tabula · recommended 1×
python-docx · recommended 1×

CATEGORY QUERY
How to extract structured data from PDF, DOCX, and PPTX documents programmatically?
you: not recommended
AI recommended (in order):
1. Apache Tika
2. Microsoft Azure Form Recognizer / Document Intelligence
3. Google Cloud Document AI
4. Tabula
5. python-docx
6. python-pptx
7. PDFMiner.six
AI recommended 7 alternatives but never named run-llama/llama_cloud_services. This is the gap to close.
Show full AI answer
CATEGORY QUERY
Looking for a cloud service to process documents for knowledge management and AI applications.
you: not recommended
AI recommended (in order):
1. Google Cloud Document AI
2. Amazon Textract
3. Azure AI Document Intelligence
4. OpenText Intelligent Capture
5. Hyperscience
6. UiPath Document Understanding
AI recommended 6 alternatives but never named run-llama/llama_cloud_services. 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 run-llama/llama_cloud_services?
pass
AI named run-llama/llama_cloud_services explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
If a team adopts run-llama/llama_cloud_services in production, what risks or prerequisites should they evaluate first?
pass
AI named run-llama/llama_cloud_services 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 run-llama/llama_cloud_services solve, and who is the primary audience?
pass
AI named run-llama/llama_cloud_services 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 run-llama/llama_cloud_services. 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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Brand-free category queries5 vs 2 in Lite
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