REPOGEO REPORT · LITE

GoogleCloudPlatform/applied-ai-engineering-samples

Default branch main · commit 1298ccd5 · scanned 6/16/2026, 5:58:20 AM

GitHub: 838 stars · 219 forks

AI VISIBILITY SCORE

27 /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

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 GoogleCloudPlatform/applied-ai-engineering-samples, 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 README's opening to clarify purpose and audience

Why:

CURRENT

Welcome to the Google Cloud Applied AI Engin

COPY-PASTE FIX

This repository provides practical, production-ready code samples and notebooks for building Generative AI applications on Google Cloud Vertex AI. It focuses on applied engineering best practices for developers and MLOps engineers.

mediumtopics#2

Add more specific topics for 'code samples' and 'applied AI'

Why:

CURRENT

generative-ai, google-cloud-platform, llms, vertex-ai

COPY-PASTE FIX

generative-ai, google-cloud-platform, llms, vertex-ai, code-samples, applied-ai-engineering

mediumreadme#3

Add a 'Who is this for?' or 'Key Differentiators' section to the README

Why:

COPY-PASTE FIX

## Who is this for?
This repository is designed for AI/ML engineers, MLOps practitioners, and developers looking for concrete, production-oriented examples to implement Generative AI solutions on Google Cloud Vertex AI. Unlike general LLM libraries or theoretical courses, these samples focus on end-to-end applied engineering best practices within the Google Cloud ecosystem.

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 GoogleCloudPlatform/applied-ai-engineering-samples

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

OpenAI Cookbook

Recommended in 1 of 2 queries

COMPETITOR LEADERBOARD

OpenAI Cookbook · recommended 1×
LangChain · recommended 1×
huggingface/transformers · recommended 1×
LlamaIndex · recommended 1×
DeepLearning.AI Courses · recommended 1×

CATEGORY QUERY
Where can I find practical code examples for building applications with large language models?
you: not recommended
AI recommended (in order):
1. OpenAI Cookbook
2. LangChain
3. Hugging Face Transformers (huggingface/transformers)
4. LlamaIndex
5. DeepLearning.AI Courses
AI recommended 5 alternatives but never named GoogleCloudPlatform/applied-ai-engineering-samples. This is the gap to close.
Show full AI answer
CATEGORY QUERY
How to develop generative AI solutions using cloud-based machine learning platforms?
you: not recommended
AI recommended (in order):
1. Google Cloud AI Platform (Vertex AI)
2. Amazon SageMaker
3. Microsoft Azure Machine Learning
4. Hugging Face Transformers
5. Weights & Biases (W&B)
6. RunwayML
AI recommended 6 alternatives but never named GoogleCloudPlatform/applied-ai-engineering-samples. 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 GoogleCloudPlatform/applied-ai-engineering-samples?
pass
AI did not name GoogleCloudPlatform/applied-ai-engineering-samples — 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 GoogleCloudPlatform/applied-ai-engineering-samples in production, what risks or prerequisites should they evaluate first?
pass
AI named GoogleCloudPlatform/applied-ai-engineering-samples 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 GoogleCloudPlatform/applied-ai-engineering-samples solve, and who is the primary audience?
pass
AI did not name GoogleCloudPlatform/applied-ai-engineering-samples — 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?

Embed your GEO score

Drop this badge into the README of GoogleCloudPlatform/applied-ai-engineering-samples. 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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HTML

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GoogleCloudPlatform/applied-ai-engineering-samples — 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