REPOGEO REPORT · LITE

marqo-ai/marqo

Default branch mainline · commit 37a72838 · scanned 6/20/2026, 5:01:56 PM

GitHub: 5,021 stars · 230 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

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 marqo-ai/marqo, 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 and enhance the deprecation notice in the README

Why:

CURRENT

NOTICE: Marqo's Open Source project is deprecated and will no longer recieve updates. To explore Marqo's product search and discovery platform, go to <a href="https://marqo.ai/">marqo.ai</a>

COPY-PASTE FIX

🚨 **NOTICE: This Marqo Open Source project is deprecated and no longer receives updates.** For Marqo's active product search and discovery platform, please visit [marqo.ai](https://marqo.ai/).

(Place this at the very top of the README, before any other content.)

mediumreadme#2

Add a 'What Marqo Was (and Was Not)' section to the README

Why:

COPY-PASTE FIX

### What Marqo Was (and Was Not)
Marqo was designed as a complete, AI-native search and discovery *platform* for e-commerce, integrating semantic search, personalization, and product recommendations. It is distinct from:
*   **Generic Vector Databases/Embedding APIs** (e.g., Pinecone, Weaviate, OpenAI Embeddings): Marqo provided an end-to-end solution, not just a component for vector storage or generation.
*   **Broad E-commerce Marketing/Personalization Suites** (e.g., Algolia Recommend, Segment): While offering personalization, Marqo's core focus was deep, AI-powered product search relevance.

lowabout#3

Update the repository description (about section)

Why:

CURRENT

Ecommerce Search and Discovery - marqo.ai

COPY-PASTE FIX

DEPRECATED: Open-source project for AI-native Ecommerce Search and Discovery. For active platform, see marqo.ai

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 marqo-ai/marqo

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

OpenAI Embeddings

Recommended in 1 of 2 queries

COMPETITOR LEADERBOARD

OpenAI Embeddings · recommended 1×
Pinecone · recommended 1×
Sentence Transformers · recommended 1×
Weaviate · recommended 1×
Cohere Embeddings · recommended 1×

CATEGORY QUERY
How to implement AI-powered semantic search for an e-commerce product catalog?
you: not recommended
AI recommended (in order):
1. OpenAI Embeddings
2. Pinecone
3. Sentence Transformers
4. Weaviate
5. Cohere Embeddings
6. Qdrant
7. Hugging Face Transformers
8. Milvus
9. Elasticsearch
10. Google Cloud Vertex AI Matching Engine
AI recommended 10 alternatives but never named marqo-ai/marqo. This is the gap to close.
Show full AI answer
CATEGORY QUERY
Looking for a platform to enhance e-commerce product discovery with personalized recommendations.
you: not recommended
AI recommended (in order):
1. Algolia Recommend
2. Segment
3. Dynamic Yield
4. Braze
5. Bloomreach Engagement
6. Recombee
7. Nosto
8. Optimizely
AI recommended 8 alternatives but never named marqo-ai/marqo. 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 marqo-ai/marqo?
pass
AI named marqo-ai/marqo explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
If a team adopts marqo-ai/marqo in production, what risks or prerequisites should they evaluate first?
pass
AI named marqo-ai/marqo 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 marqo-ai/marqo solve, and who is the primary audience?
pass
AI named marqo-ai/marqo 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 marqo-ai/marqo. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

Live preview

MARKDOWN (README)

[![RepoGEO](https://repogeo.com/badge/marqo-ai/marqo.svg)](https://repogeo.com/en/r/marqo-ai/marqo)

HTML

<a href="https://repogeo.com/en/r/marqo-ai/marqo"><img src="https://repogeo.com/badge/marqo-ai/marqo.svg" alt="RepoGEO" /></a>

Pro

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marqo-ai/marqo — 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