Elicit - The Ultimate AI Research Assistant

Overview:

      Elicit is a web-based platform that uses machine learning to automate and enhance research workflows. It helps researchers find relevant papers, extract key information, and synthesize their findings in a fast and efficient way.

Users:

      Elicit is designed for researchers from various domains, such as biomedicine, machine learning, social sciences, and more. It is trusted by over 800,000 researchers from leading institutions and organizations.

Goal:

      Elicit's goal is to empower researchers with the best tools and data to conduct high-quality research and advance scientific knowledge. Elicit aims to make research easier, faster, and more enjoyable.

Uses and Features:

1. Literature Review: Elicit can speed up the process of finding and reviewing relevant papers for any research topic. It can search across 200 million academic papers from the Semantic Scholar corpus, which covers all academic disciplines. It can also find papers that are not easily accessible through keyword searches, by using natural language queries and semantic similarity.
2. Data Extraction: Elicit can extract key information from papers, such as authors, abstracts, results, figures, tables, and more. It can also generate summaries, comparisons, and insights from the extracted data, using natural language generation and data visualization techniques.
3. Synthesis: Elicit can help researchers synthesize their findings and communicate them effectively. It can generate reports, presentations, and publications from the data and insights obtained from the previous steps. It can also provide feedback and suggestions to improve the quality and clarity of the output.
4. Collaboration: Elicit can facilitate collaboration among researchers by allowing them to share their work, comment on each other's projects, and join communities of interest. Elicit also integrates with popular tools and platforms, such as Google Drive, Dropbox, Slack, and GitHub.
5. Customization: Elicit can be customized to fit the specific needs and preferences of each researcher. It allows users to create their own workflows, add their own data sources, fine-tune the models, and adjust the settings and parameters.

How it Works:

1. Sign Up: Users can sign up for Elicit for free, using their email, Google, or GitHub account. They will receive 5,000 credits to use on the platform. They can also subscribe to Elicit Plus, which offers more features and monthly credits.
2. Create a Project: Users can create a new project by entering a name, a description, and a research question. They can also choose a domain and a language for their project.
3. Run Workflows: Users can run various workflows to perform different tasks, such as finding papers, extracting data, generating summaries, and more. They can also add columns to their tables to display additional information or perform calculations.
4. Analyze Results: Users can view and analyze the results of their workflows in various formats, such as tables, charts, graphs, maps, and more. They can also export, download, or share their results with others.
5. Generate Output: Users can generate various types of output from their results, such as reports, presentations, and publications. They can also edit, format, and style their output using the built-in editor or their preferred tool.

Customer Companies and Statistics:

1. Elicit is used by researchers from leading institutions and organizations, such as MIT, Stanford, Harvard, Google, Microsoft, IBM, and more.
2. Elicit has a 4.8/5 rating on Product Hunt, based on 237 reviews.
3. Elicit has processed over 10 million papers and generated over 1 million summaries, insights, and reports for its users.
4. Elicit has won several awards and recognitions, such as the Best AI Startup Award at the AI Summit 2023, the Top 10 AI Tools for Researchers by Forbes, and the Featured Product of the Month by Product Hunt.
5. Elicit is constantly improving and expanding its features and capabilities, by incorporating the latest research and technologies in machine learning, natural language processing, and data science.