Now with multi-model reasoning

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Features

Everything you need to think clearly

A research workspace that reads, reasons, and remembers — so you can spend your time deciding, not digging.

01

Ask in plain language

Pose a question the way you’d ask a colleague. Atlas searches millions of papers, reports, and your own files at once.

02

Every claim, cited

Inline citations link straight back to the source sentence. Hover to verify, click to read the original.

03

Multi-model intelligence

Each question is routed to the model that answers it best — reasoning, retrieval, or raw speed.

04

Living documents

Briefs that update themselves. When new research lands, your summary quietly catches up.

05

Your knowledge, connected

Drop in PDFs, links, and notes. Atlas builds a map of what you know and what’s missing.

06

Share-ready in seconds

Turn any thread into a polished brief, a deck, or a link your whole team can open.

How it works

From question to answer in three moves

01

Ask or upload

Type a question in plain language, or drop in the documents you’re working from.

02

Atlas synthesizes

It reads across every source, compares findings, and assembles a cited answer in seconds.

03

Ship the work

Export a brief, share a live link, or keep pulling the thread deeper. It’s yours.

The workspace

A single surface for everything you’re researching

atlas.research/workspace
What are the leading approaches to retrieval-augmented research?

Three approaches dominate the recent literature. [1] Dense retrieval pairs neural embeddings with a re-ranking pass; [2] hybrid systems blend keyword and vector search for precision; and [3] agentic pipelines let the model plan its own multi-step lookups.

For long-form synthesis, agentic pipelines consistently produce the most complete answers, at the cost of latency. [4]

4 sources
1
Dense Passage Retrieval for Open-Domain QA
arXiv · 2020
2
Hybrid Search at Scale
Pinecone · 2024
3
ReAct: Reasoning + Acting in LLMs
arXiv · 2023
4
Self-RAG: Learning to Retrieve & Critique
arXiv · 2023