Petal

Petal is a document-centered research workspace that helps people organize technical material and interrogate it with generative AI. Instead of treating every question as a general web query, it works from documents placed in a user-controlled knowledge collection. This makes it useful for reviewing papers, comparing evidence, locating details, and producing answers that remain tied to the underlying sources.

Highlights

• Chat with an individual document or search for answers across multiple documents
• Receive source-backed responses that make supporting material easier to inspect
• Store research files in a centralized cloud library with automatic metadata extraction
• Highlight passages, add comments, share collections, and collaborate with guests
• Create citation lists and use AI-assisted writing and structured table features on eligible plans

Petal is aimed primarily at researchers, students, faculty members, R&D groups, and professional teams that regularly work with dense collections of literature or internal documents. A permanent free plan includes limited storage, collections, annotations, single-document chat, and a fixed allocation of AI credits. Paid individual plans expand storage, recurring AI usage, export options, and advanced multi-document features, while organizational licensing is available separately.