AgentIndex icon
AgentIndex
pensyve logo
pensyve
★ 97
vs
deep-research logo
deep-research
★ 4.7k

pensyve vs deep-research

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.; deep-research: Deep Research is an AI-powered tool designed to generate comprehensive research reports rapidly, leveraging advanced AI models and internet connectivity. It prioritizes user privacy by processing and storing all data locally.

01

TL;DR

pensyve logo
pensyveRAG / Knowledge Base · ★ 97

Persist agent knowledge across sessions and avoid repetitive questions

Read pensyve full review →
deep-research logo
deep-researchRAG / Knowledge Base · ★ 4.7k

Rapidly generate in-depth research reports for personal and professional use.

Read deep-research full review →
02

Side-by-Side Comparison

Field
pensyve logopensyve
deep-research logodeep-research
Category
RAG / Knowledge Base
RAG / Knowledge Base
Stars
★ 97
★ 4.7k
License
NOASSERTION
MIT
Install Command
pip install pensyve
docker run -d --name deep-research -p 3333:3000 xiangfa/deep-research
Updated
1d ago
4mo ago
Open Source
Yes
Yes
Website
↗ Visit
↗ Visit
GitHub
↗ GitHub
↗ GitHub
Tags
agent-memory, ai, ai-agents
AI Research, LLM, Privacy-focused
03

Features

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
deep-research logodeep-research
01Rapidly generates comprehensive research reports in minutes.
02Ensures privacy by processing and storing all data locally in the browser.
03Supports a wide range of mainstream large language models (LLMs).
04Integrates with various web search engines for enhanced information gathering.
05Allows uploading and processing local files to build a knowledge base.
04

Use Cases

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
deep-research logodeep-research
↳Rapidly generate in-depth research reports for personal and professional use.
↳Serve as a deep research as a service (SaaS) platform via SSE API.
↳Integrate deep research functionality into other AI applications using MCP.
FAQ

FAQ

What is the difference between pensyve and deep-research?
Both pensyve and deep-research are in the RAG / Knowledge Base category. pensyve has 97 stars, while deep-research has 4.7k stars.
Which is better, pensyve or deep-research?
The best choice depends on your use case. Choose pensyve if Persist agent knowledge across sessions and avoid repetitive questions, and deep-research if Rapidly generate in-depth research reports for personal and professional use..
Is pensyve free or open source?
Yes, pensyve is open source on GitHub (NOASSERTION).
Is deep-research free or open source?
Yes, deep-research is open source on GitHub (MIT).
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