Petal is a document intelligence platform designed to help individuals and teams manage, annotate, and extract insights from large collections of documents, particularly academic papers and PDFs. Users can upload documents to a centralized workspace, organize them into collections, and use AI-assisted search and question-answering to surface relevant information quickly. The platform supports collaborative workflows, allowing multiple users to share document libraries, highlight passages, and add notes. Petal's AI capabilities enable users to ask natural-language questions against their document corpus and receive cited answers drawn directly from the uploaded content. It is positioned for research-heavy workflows in academia, professional services, and knowledge-intensive business teams who need to synthesize information across many sources without manually reading every document.
Target audience and deployment
- Solo / Freelancer
- Startup
- SMB
- Mid-market
- Cloud
Key features
Use cases
- Search across large document libraries
- Annotate and highlight research documents
- Collaborate on shared document workspaces
- Ask AI questions against uploaded content
- Organize research into structured collections
Best for
- Researchers who need to synthesize insights across large volumes of academic papers
- Knowledge workers who need to quickly locate information within extensive document libraries
- Teams who need to collaborate on shared research and annotate documents together
- Analysts who need AI-assisted answers drawn from proprietary or curated document sets