REPOGEO REPORT · LITE

morphik-org/morphik-core

Default branch main · commit 03a93e89 · scanned 5/23/2026, 10:47:39 AM

GitHub: 3,599 stars · 304 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

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 morphik-org/morphik-core, 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 production readiness

Why:

CURRENT

The README currently starts with badges and a migration notice, followed by an H2: "Morphik is a AI-native toolset for visually rich documents and multimodal data".

COPY-PASTE FIX

Morphik Core is a production-ready, AI-native toolset for highly accurate document search and storage, specifically designed for visually rich and multimodal data in AI applications. It provides an end-to-end solution for integrating complex context into your AI applications, moving beyond traditional RAG limitations.

mediumtopics#2

Add more specific topics to improve category visibility

Why:

CURRENT

artificial-intelligence, cache-augmented-generation, colpali, database, litellm, multimodal, rag, rules-based-ingestion

COPY-PASTE FIX

artificial-intelligence, cache-augmented-generation, colpali, database, litellm, multimodal, rag, rules-based-ingestion, vector-database, document-store, rag-framework, ai-search

mediumreadme#3

Clarify the project's license in the README

Why:

COPY-PASTE FIX

## License 
 Morphik Core is released under the terms outlined in the LICENSE file. Please refer to the LICENSE file for specific details regarding usage and distribution.

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 morphik-org/morphik-core

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

Pinecone

Recommended in 2 of 2 queries

COMPETITOR LEADERBOARD

Pinecone · recommended 2×
weaviate/weaviate · recommended 1×
qdrant/qdrant · recommended 1×
milvus-io/milvus · recommended 1×
elastic/elasticsearch · recommended 1×

CATEGORY QUERY
How to effectively store and search multimodal data for AI-powered applications?
you: not recommended
AI recommended (in order):
1. Pinecone
2. Weaviate (weaviate/weaviate)
3. Qdrant (qdrant/qdrant)
4. Milvus (milvus-io/milvus)
5. Elasticsearch (elastic/elasticsearch)
6. Faiss (facebookresearch/faiss)
7. PostgreSQL (pgvector/pgvector)
AI recommended 7 alternatives but never named morphik-org/morphik-core. This is the gap to close.
Show full AI answer
CATEGORY QUERY
What are the best tools for RAG with complex, unstructured documents and visual data?
you: not recommended
AI recommended (in order):
1. LlamaIndex
2. LangChain
3. Weaviate
4. Pinecone
5. Milvus
6. OpenAI's CLIP
7. Unstructured.io
AI recommended 7 alternatives but never named morphik-org/morphik-core. 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 morphik-org/morphik-core?
pass
AI did not name morphik-org/morphik-core — 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 morphik-org/morphik-core in production, what risks or prerequisites should they evaluate first?
pass
AI named morphik-org/morphik-core 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 morphik-org/morphik-core solve, and who is the primary audience?
pass
AI did not name morphik-org/morphik-core — 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 morphik-org/morphik-core. 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/morphik-org/morphik-core.svg)](https://repogeo.com/en/r/morphik-org/morphik-core)

HTML

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

Pro

Subscribe to Pro for deep diagnoses

morphik-org/morphik-core — 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