Elicit?

NOT REALLYA prototype of the interface is possible, but the durable product depends on difficult systems beyond the UI. Build a safer adjacent workflow instead.

BUILD FIRST

A non-sensitive or read-only version of the core experience
A manual review step wherever correctness or trust matters
A narrow companion tool that removes a real piece of work

LEAVE FOR LATER

Regulated decisions, payments, or irreversible actions
Claims of correctness, compliance, or uptime that the MVP cannot support
Sensitive integrations until security, support, and auditability are ready

RESEARCH NOTES

What this tool actually does.

Checked 2026-09-06

Elicit is an AI-powered research assistant for scientific literature, not a read-it-later app. Its official site describes it as "AI for scientific research" that lets users search, summarize, extract data from, and chat with over 125 million papers. Used by over 2 million researchers in academia and industry, it includes a Library feature where users store and organize sources found during research. The core workflow centers on finding relevant academic papers and pulling structured information from them, rather than saving articles for later reading. The catalog verdict "not_really" is correct: the product is misclassified as read-it-later.

SOURCES

RESEARCHED BUILD PROMPT

Give this to your coding agent.

Build a web application that replaces the core workflow of Elicit, the AI scientific research assistant. The user flow: (1) A researcher enters a research question (e.g., "What interventions reduce postoperative delirium?"). (2) The app searches a large corpus of academic papers and returns a ranked list with metadata (title, authors, year, journal, abstract, relevance score). (3) The user selects papers and defines an extraction table with custom columns (e.g., study design, sample size, effect size). (4) The app uses an LLM to fill the table from each paper's abstract/full text with strict structured output. (5) The user can chat with the selected papers, with the LLM grounding answers in retrieved content and citing sources. (6) Saved papers appear in a Library section. User-facing requirements: query input screen, results list with filtering by year/venue, table builder with editable schemas and CSV export, citation-scoped chat panel, Library with tags and notes. Technical requirements: a modern stack (Next.js + React or FastAPI + React), LLM API integration (OpenAI/Anthropic or local via Ollama) for summarization, extraction, and chat; a vector database (pgvector or LanceDB) for semantic search over paper embeddings; open-access paper index via Semantic Scholar API or PubMed/arXiv APIs; background job queue for embedding and extraction; database schema for papers, sessions, extraction templates, library items. Do not copy Elicit's brand, logo, color palette, or UI layout; create an original interface. Out of scope: PDF parsing of paywalled content, full citation graph exploration, multi-user collaboration, mobile apps, browser extensions, auto-generated literature review manuscripts. Include a README with setup instructions, environment variables, API-rate-limit notes, and known limitations: hallucination risk in extracted data, corpus coverage limited to open-access APIs, extraction accuracy degraded on tables/figures, and API cost considerations.

Visit the official product page