RRepoGEO

REPOGEO REPORT · LITE

agiresearch/A-mem

Default branch main · commit ceffb860 · scanned 6/21/2026, 9:58:13 AM

GitHub: 1,059 stars · 114 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
35 /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
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 agiresearch/A-mem, 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 differentiator in the README's introduction

    Why:

    CURRENT
    A novel agentic memory system for LLM agents that can dynamically organize memories in an agentic way.
    COPY-PASTE FIX
    A novel agentic memory system for LLM agents that can dynamically organize memories in an agentic way. Unlike standalone vector databases or general LLM frameworks, A-MEM provides a complete, agent-driven system for dynamic memory organization, evolution, and retrieval, leveraging tools like ChromaDB for intelligent indexing.
  • mediumtopics#2
    Add more specific topics to improve categorization

    Why:

    CURRENT
    agent, llm, memory
    COPY-PASTE FIX
    agent, llm, memory, agentic-ai, llm-agents, long-term-memory, knowledge-management, zettelkasten
  • mediumhomepage#3
    Add a homepage URL to the repository's About section

    Why:

    COPY-PASTE FIX
    https://[INSERT_A-MEM_PROJECT_OR_PAPER_URL_HERE]

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 agiresearch/A-mem
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Pinecone
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Pinecone · recommended 2×
  2. LangChain · recommended 1×
  3. Weaviate · recommended 1×
  4. Chroma · recommended 1×
  5. Qdrant · recommended 1×
  • CATEGORY QUERY
    How to implement advanced, dynamic memory management for large language model agents?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. Pinecone
    3. Weaviate
    4. Chroma
    5. Qdrant
    6. LlamaIndex
    7. Neo4j
    8. ArangoDB
    9. Redis
    10. Redis Stack
    11. Faiss

    AI recommended 11 alternatives but never named agiresearch/A-mem. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are the best systems for organizing long-term memory in autonomous LLM agents?
    you: not recommended
    AI recommended (in order):
    1. Chroma (chroma-core/chroma)
    2. Pinecone
    3. Weaviate (weaviate/weaviate)
    4. Qdrant (qdrant/qdrant)
    5. Milvus (milvus-io/milvus)
    6. Redis (redis/redis)
    7. PostgreSQL

    AI recommended 7 alternatives but never named agiresearch/A-mem. 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 agiresearch/A-mem?
    pass
    AI named agiresearch/A-mem explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • If a team adopts agiresearch/A-mem in production, what risks or prerequisites should they evaluate first?
    pass
    AI named agiresearch/A-mem 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 agiresearch/A-mem solve, and who is the primary audience?
    pass
    AI named agiresearch/A-mem explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

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agiresearch/A-mem — 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