AgentIndex icon
AgentIndex
hyperresearch logo
hyperresearch
★ 4.2k
vs
deep-research logo
deep-research
★ 4.7k

hyperresearch vs deep-research

hyperresearch: Hyperresearch is a deep research harness installed into Claude Code or OpenAI Codex, running a tier-adaptive 16-step pipeline that turns one prompt into an adversarially audited report with full source provenance. Every source it reads is stored in a searchable markdown-plus-SQLite vault that later sessions reuse.; 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

hyperresearch logo
hyperresearchRAG / Knowledge Base · ★ 4.2k

Produce a sourced competitor or market analysis

Read hyperresearch 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
hyperresearch logohyperresearch
deep-research logodeep-research
Category
RAG / Knowledge Base
RAG / Knowledge Base
Stars
★ 4.2k
★ 4.7k
License
MIT
MIT
Install Command
pip install hyperresearch && hyperresearch 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
deep-research, claude-code, codex
AI Research, LLM, Privacy-focused
03

Features

hyperresearch logohyperresearch
0116-step pipeline with a fast path for bounded questions
02Cite-checker verifies each citation supports its sentence before the report ships
03One search across OpenAlex, Crossref, CORE, ClinicalTrials.gov, SEC EDGAR and FRED
04Fetches legal open-access copies of paywalled papers via Unpaywall, Europe PMC and CORE
05Persistent source vault and resumable runs
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

hyperresearch logohyperresearch
↳Produce a sourced competitor or market analysis
↳Run a literature review across papers, trials and filings
↳Build up a reusable research vault for a project
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 hyperresearch and deep-research?
Both hyperresearch and deep-research are in the RAG / Knowledge Base category. hyperresearch has 4.2k stars, while deep-research has 4.7k stars.
Which is better, hyperresearch or deep-research?
The best choice depends on your use case. Choose hyperresearch if Produce a sourced competitor or market analysis, and deep-research if Rapidly generate in-depth research reports for personal and professional use..
Is hyperresearch free or open source?
Yes, hyperresearch is open source on GitHub (MIT).
Is deep-research free or open source?
Yes, deep-research is open source on GitHub (MIT).
Cloud Infrastructure
Ad

Deploy on DigitalOcean

Host your MCP servers, Docker containers, and AI agents with $200 free credit over 60 days.

Claim $200 Free Credit
→

Related

Alternatives to hyperresearch →Alternatives to deep-research →hyperresearch details →deep-research details →