crystalline logo
crystalline
★ 17
vs
deep-research logo
deep-research
★ 4.7k

crystalline vs deep-research

crystalline: Crystalline provides AI agents with crystallized intelligence, allowing them to accumulate and retain knowledge across sessions, unlike an LLM's fluid intelligence. It acts as a local search index on plain markdown files, enabling agents to onboard curated knowledge and capture new learnings, evolving from a stranger to a peer.; 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

crystalline logo
crystallineRAG / Knowledge Base · ★ 17

Onboard AI agents with curated domain-specific knowledge at the start of each session.

deep-research logo
deep-researchRAG / Knowledge Base · ★ 4.7k

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

02

Side-by-Side Comparison

Field
crystalline logocrystalline
deep-research logodeep-research
Category
RAG / Knowledge Base
RAG / Knowledge Base
Stars
★ 17
★ 4.7k
License
AGPL-3.0
MIT
Install Command
brew install jordiboehme/tap/crystalline && crystalline install claude-code && mkdir -p ~/knowledge/engineering && crystalline domain init ~/knowledge/engineering --name engineering && crystalline domain add engineering ~/knowledge/engineering
docker run -d --name deep-research -p 3333:3000 xiangfa/deep-research
Updated
1d ago
4mo ago
Open Source
Yes
Yes
Tags
AI Agents, Knowledge Base, RAG
AI Research, LLM, Privacy-focused
03

Features

crystalline logocrystalline
01Structured knowledge organization using domains (folders) and engrams (markdown files).
02Hybrid search combining full-text and semantic ranking for efficient knowledge retrieval.
03Fluid web UI for human-agent collaboration, enabling reading, editing, and managing knowledge.
04Supports GitHub-based team collaboration with review workflows for shared knowledge.
05Knowledge graph and temporal filtering to understand relationships and time-bounded facts.
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

crystalline logocrystalline
↳Onboard AI agents with curated domain-specific knowledge at the start of each session.
↳Enable AI agents to capture and persist new observations, decisions, and lessons learned from their work.
↳Facilitate team knowledge sharing and collaboration on a continually growing and evolving knowledge base.
↳Reduce redundancy and repeated explanations by providing agents with access to accumulated 'crystallized intelligence'.
↳Efficiently retrieve specific facts or context from a large collection of knowledge units based on task routing.
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 crystalline and deep-research?
Both crystalline and deep-research are in the RAG / Knowledge Base category. crystalline has 17 stars, while deep-research has 4.7k stars.
Which is better, crystalline or deep-research?
The best choice depends on your use case. Choose crystalline if Onboard AI agents with curated domain-specific knowledge at the start of each session., and deep-research if Rapidly generate in-depth research reports for personal and professional use..
Is crystalline free or open source?
Yes, crystalline is open source on GitHub (AGPL-3.0).
Is deep-research free or open source?
Yes, deep-research is open source on GitHub (MIT).
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