An open-source framework for programming and optimizing language-model pipelines.
Reviewed use-case guide
Research tools differ in source coverage, citation transparency, document support, and the amount of human verification they require. These profiles emphasize traceable sources and practical research workflows.
An open-source framework for programming and optimizing language-model pipelines.
An open-source Python framework for retrieval, agents, and production AI pipelines.
An AI-assisted notes workspace for capture, organization, and retrieval.
A search and extraction API built for agents and AI applications.
A computational knowledge engine for factual and mathematical queries.
A literature discovery tool for mapping, monitoring, and organizing papers.
A visual tool for exploring papers related through citation patterns.
A free scientific literature search and discovery platform.
A research platform that analyzes how scientific papers are cited.
A code assistant that uses repository context for search, chat, and editing.
A conversational search engine designed around direct answers and source pages.
An AI search and productivity service for cited research and task workflows.
A Microsoft AI assistant for web, writing, creation, and everyday tasks.
A literature-discovery workspace for exploring papers, authors, citations, and visual research networks.
An AI meeting agent for transcription, summaries, action items, searchable knowledge, and follow-up workflows.
AI agents, writing assistance, search, and meeting workflows integrated with a Notion workspace.
Google's source-grounded research and thinking tool for analyzing documents and creating cited outputs.
A framework and managed platform for document ingestion, retrieval, workflows, and knowledge agents.
An AI research assistant for finding papers, extracting evidence, and supporting systematic literature reviews.
A conversational assistant from OpenAI.
An AI assistant from Anthropic.
Google's AI assistant and model family.
An answer engine for web research.
No. They can accelerate discovery and synthesis, but important claims still need to be checked against primary sources and the original documents.