AgentIndex icon
AgentIndex
Ori-Mnemos logo
Ori-Mnemos
★ 333
vs
pensyve logo
pensyve
★ 97

Ori-Mnemos vs pensyve

Ori-Mnemos: Ori Mnemos is an open-source persistent memory infrastructure for AI agents that implements human cognition models on a knowledge graph. It uses ACT-R decay, spreading activation, and Hebbian learning to manage memory, and achieves state-of-the-art retrieval performance while being zero-infrastructure and portable.; pensyve: Pensyve is a universal memory runtime for AI agents that eliminates amnesia across sessions. It offers three memory types (episodic, semantic, procedural), 8-signal fusion retrieval, and FSRS-based forgetting curve. Framework-agnostic with SDKs for Python, TypeScript, Go, and integrations with LangChain, CrewAI, AutoGen, plus native plugins for Claude Code, Cursor, and VS Code.

01

TL;DR

Ori-Mnemos logo
Ori-MnemosMemory & Context · ★ 333

Multi-hop retrieval QA (e.g., HotpotQA)

Read Ori-Mnemos full review →
pensyve logo
pensyveRAG / Knowledge Base · ★ 97

Persist agent knowledge across sessions and avoid repetitive questions

Read pensyve full review →
02

Side-by-Side Comparison

Field
Ori-Mnemos logoOri-Mnemos
pensyve logopensyve
Category
Memory & Context
RAG / Knowledge Base
Stars
★ 333
★ 97
License
Apache-2.0
NOASSERTION
Install Command
npm install -g ori-memory && ori init my-agent && cd my-agent
pip install pensyve
Updated
3w ago
1d ago
Open Source
Yes
Yes
Website
↗ Visit
↗ Visit
GitHub
↗ GitHub
↗ GitHub
Tags
agent-memory, ai-agent, ai-agents
agent-memory, ai, ai-agents
03

Features

Ori-Mnemos logoOri-Mnemos
01Persistent memory across sessions, clients, and machines
02Knowledge graph with wiki-links, PageRank, and community detection
03Three memory spaces with cognitive forgetting (ACT-R decay)
04Four-signal fusion retrieval (semantic, BM25, PageRank, warmth)
05Retrieval intelligence with Q-learning and meta-learning
pensyve logopensyve
01Three memory types: episodic, semantic, procedural
028-signal fusion retrieval (vector, BM25, graph, intent, recency, frequency, confidence, type boost)
03FSRS forgetting curve with reinforcement for natural decay
04Offline-first with SQLite and ONNX embeddings, no cloud required
05Framework-agnostic with SDKs for Python, TypeScript, Go, and MCP
04

Use Cases

Ori-Mnemos logoOri-Mnemos
↳Multi-hop retrieval QA (e.g., HotpotQA)
↳Long-term conversational memory (e.g., LoCoMo)
↳Persistent AI agent identity and knowledge
pensyve logopensyve
↳Persist agent knowledge across sessions and avoid repetitive questions
↳Integrate memory into any AI framework (LangChain, CrewAI, AutoGen) via adapters
↳Enable agents to learn effective strategies through procedural memory
FAQ

FAQ

What is the difference between Ori-Mnemos and pensyve?
Both Ori-Mnemos and pensyve are in the Memory & Context category. Ori-Mnemos has 333 stars, while pensyve has 97 stars.
Which is better, Ori-Mnemos or pensyve?
The best choice depends on your use case. Choose Ori-Mnemos if Multi-hop retrieval QA (e.g., HotpotQA), and pensyve if Persist agent knowledge across sessions and avoid repetitive questions.
Is Ori-Mnemos free or open source?
Yes, Ori-Mnemos is open source on GitHub (Apache-2.0).
Is pensyve free or open source?
Yes, pensyve is open source on GitHub (NOASSERTION).
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