openmemind

openmemind / memind

Public

Self-evolving cognitive memory for AI agents in Java. Empowering 24/7 proactive agents like OpenClaw with understanding.

ai ai-agent ai-agents java memory
11
0
100% credibility
Found Mar 20, 2026 at 11 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Java
AI Summary

Memind is a Java-based cognitive memory system that automatically extracts, organizes, and evolves hierarchical insights from AI agent conversations.

How It Works

1
📖 Discover Memind

You find Memind, a helper that makes AI friends remember conversations deeply and smartly.

2
🧩 Add to your project

You easily add Memind to your AI project so it can start building memories.

3
🔗 Connect AI service

You link a smart thinking service, like an AI brain, to power the memory magic.

4
💬 Share chat histories

You feed in real conversations, and Memind quietly organizes facts into growing insights.

5
🌳 Memories evolve

Watch as simple facts turn into patterns, profiles, and deep understandings automatically.

6
❓ Ask smart questions

You query things like 'What does this person like?' and get rich, connected answers.

🎉 AI truly remembers

Your AI now understands people deeply, predicts needs, and acts wisely every time.

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Star Growth

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AI-Generated Review

What is memind?

Memind builds self-evolving cognitive memory for AI agents in Java, turning raw conversations into a hierarchical Insight Tree that automatically extracts facts, patterns, and deep user profiles. It solves flat, non-evolving storage in agent memory by progressively distilling knowledge across leaf, branch, and root levels for true understanding in 24/7 proactive agents. Drop in the Spring Boot starter, feed it messages via a simple API like `memory.addMessages(memoryId, messages)`, and query with natural language retrieval.

Why is it gaining traction?

It hits SOTA on the LoCoMo benchmark using just gpt-4o-mini, proving smart architecture beats big models, while being the first Java-native option for enterprise stacks with Spring AI integration. Developers dig the fully automatic pipeline—no manual management—and dual retrieval modes: fast vector/BM25 hybrid or LLM-deep reasoning. For self-evolving AI agents on GitHub, it stands out by enabling cognitive evolution without constant retraining.

Who should use this?

Java backend devs building persistent AI agents, like customer support bots tracking user profiles over sessions or dev tools remembering tool stats and workflows. Ideal for teams wanting 24/7 agents that adapt to user behavior, preferences, and events without key-value drudgery. Skip if you're in Python ecosystems or need instant production scale.

Verdict

Promising for Java AI agent builders seeking self-evolving cognitive memory, but at 11 stars and 1.0% credibility, it's early—docs are solid with examples, but expect rough edges in stability. Prototype it now if you're in Spring AI; hold for 1.0 release otherwise.

(198 words)

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