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Description
CiteDash is an innovative research and writing platform powered by artificial intelligence, aimed at enhancing the academic workflow by integrating source discovery, analysis, drafting, and citation functionalities into a cohesive system. Users can simply input a research topic, essay prompt, or inquiry, prompting a sophisticated multi-agent pipeline to automatically explore various academic databases like Semantic Scholar, PubMed, and OpenAlex to identify, assess, and synthesize pertinent literature into a well-organized draft complete with inline citations. By focusing on accuracy and reliability, CiteDash ensures that every assertion is backed by verifiable academic sources, effectively eliminating fabricated references and guaranteeing that outputs can be traced back to authentic studies. The platform accommodates an extensive variety of academic tasks, such as writing essays, developing research papers, conducting literature reviews, and preparing for exams, while providing useful features like AI-generated notes, organized outlines, and question generation for active recall, all aimed at enhancing the learning experience. Furthermore, this comprehensive approach not only saves time but also elevates the quality of academic work by facilitating a deeper understanding of the subject matter.
Description
FutureHouse is a nonprofit research organization dedicated to harnessing AI for the advancement of scientific discovery in biology and other intricate disciplines. This innovative lab boasts advanced AI agents that support researchers by speeding up various phases of the research process. Specifically, FutureHouse excels in extracting and summarizing data from scientific publications, demonstrating top-tier performance on assessments like the RAG-QA Arena's science benchmark. By utilizing an agentic methodology, it facilitates ongoing query refinement, re-ranking of language models, contextual summarization, and exploration of document citations to improve retrieval precision. In addition, FutureHouse provides a robust framework for training language agents on demanding scientific challenges, which empowers these agents to undertake tasks such as protein engineering, summarizing literature, and executing molecular cloning. To further validate its efficacy, the organization has developed the LAB-Bench benchmark, which measures language models against various biology research assignments, including information extraction and database retrieval, thus contributing to the broader scientific community. FutureHouse not only enhances research capabilities but also fosters collaboration among scientists and AI specialists to push the boundaries of knowledge.
API Access
Has API
API Access
Has API
Integrations
Discord
EndNote
Google Sheets
Markdown
Mendeley
Microsoft Excel
Microsoft Word
Model Context Protocol (MCP)
Node.js
PubMed
Integrations
Discord
EndNote
Google Sheets
Markdown
Mendeley
Microsoft Excel
Microsoft Word
Model Context Protocol (MCP)
Node.js
PubMed
Pricing Details
$9 per month
Free Trial
Free Version
Pricing Details
No price information available.
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
CiteDash
Country
United States
Website
citedash.ai/
Vendor Details
Company Name
FutureHouse
Founded
2023
Country
United States
Website
www.futurehouse.org