AgentIndex icon
AgentIndex
wenlan logo
wenlan
★ 86
vs
deep-research logo
deep-research
★ 4.7k

wenlan vs deep-research

wenlan: Wenlan is a living personal knowledge library for the AI-native age, built by your agents and grounded in its sources. It continuously evolves between sessions, distilling captures into source-cited wiki pages that feed retrieval.; 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

wenlan logo
wenlanRAG / Knowledge Base · ★ 86

Capture decisions, lessons, and facts from AI agent interactions to build a persistent knowledge base.

Read wenlan 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
wenlan logowenlan
deep-research logodeep-research
Category
RAG / Knowledge Base
RAG / Knowledge Base
Stars
★ 86
★ 4.7k
License
Apache-2.0
MIT
Install Command
npx -y wenlan setup && ~/.wenlan/bin/wenlan install
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
AI Agent Memory, Personal Knowledge Management, RAG
AI Research, LLM, Privacy-focused
03

Features

wenlan logowenlan
01Trustworthy and source-cited knowledge pages, with hallucination prevention and fact deduplication.
02Self-evolving knowledge base that updates and refines between sessions without manual maintenance.
03Real Git versioning for all memories, pages, and sessions, enabling inspection, diff, and revert.
04Unified local daemon serving context to multiple MCP-compatible AI clients.
05Hybrid retrieval system leveraging vector embeddings, FTS5, and graph context for relevant recall.
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

wenlan logowenlan
↳Capture decisions, lessons, and facts from AI agent interactions to build a persistent knowledge base.
↳Maintain continuous, topic-relevant context across multiple AI agent sessions and projects.
↳Distill raw agent captures and existing documents into trustworthy, source-cited wiki pages.
↳Integrate a shared memory and context layer across various AI development environments like Claude Code, Cursor, and VS Code.
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 wenlan and deep-research?
Both wenlan and deep-research are in the RAG / Knowledge Base category. wenlan has 86 stars, while deep-research has 4.7k stars.
Which is better, wenlan or deep-research?
The best choice depends on your use case. Choose wenlan if Capture decisions, lessons, and facts from AI agent interactions to build a persistent knowledge base., and deep-research if Rapidly generate in-depth research reports for personal and professional use..
Is wenlan free or open source?
Yes, wenlan is open source on GitHub (Apache-2.0).
Is deep-research free or open source?
Yes, deep-research is open source on GitHub (MIT).
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