What is Petal?
Petal is an AI research assistant that lets users chat with their own documents and get fully sourced answers. It combines cloud document storage, AI-powered document analysis, multi-document chat, citation generation, and collaborative workspaces. Researchers, academics, and corporate R&D teams use it to extract insights from large document libraries. All AI outputs are grounded in the user’s own uploaded knowledge base.
Features & Benefits
- Single-document AI chat – Converse with any document to extract key points, summaries, translations, and explanations. The AI research assistant answers questions using only the content of the selected document, with full source attribution.
- Multi-document AI chat – Query across an entire document library simultaneously. Surface connections, compare findings, and identify patterns across multiple research papers or reports in a single conversation.
- AI Table – Run structured analysis across multiple documents using custom criteria. Compare studies, trace influencing factors, assess methodological weaknesses, and extract measured outcomes into a single organized table.
- AI Create – Generate new research content and written outputs directly informed by the documents stored in the library.
- Cloud document library – Store and access PDFs and documents from any device. Automatic metadata extraction, file deduplication, and cross-collection syncing keep the library accurate and current.
- Document organization – Organize research using collections, tags, and detailed metadata. Unlimited collections and annotations available on paid plans.
- Annotation and collaboration – Highlight and comment directly on documents. Share workspaces with collaborators via shareable links without email-based file exchange.
- Citation generator – Generate formatted citations in 10,000+ styles including APA, MLA, Harvard, IEEE, Chicago, and Vancouver. Import references via DOI, PMID, ArXiv ID, ISBN, or URL. Export as BibTeX or to Word.
- Web importer – Capture PDFs and web pages from any browser session and save them directly to the Petal library. Available for Chrome, Firefox, and Safari.
- Microsoft Word add-in – Insert references and auto-generate bibliographies from within Word. Supports 9,000+ citation styles without leaving the document editor.
- Cross-workspace sharing – Share documents and collections across multiple workspaces for team and institutional collaboration.
- White label and enterprise license – Deploy Petal under a custom brand for institutional or large-scale enterprise use.
Real-World Applications
Academic researchers conducting literature reviews may use Petal to process large document sets without reading every paper in full. The AI Table analyzes dozens of studies against custom criteria simultaneously — extracting outcomes, comparing methodologies, and identifying research gaps in a fraction of the time manual review requires. This makes Petal a practical AI research assistant for systematic reviews and meta-analyses.
Graduate students and faculty managing active reference libraries can combine the cloud document manager with the citation generator to maintain one organized source of truth. The web importer captures papers during browser sessions. The Word add-in formats citations automatically. With 10,000+ supported citation styles, every formatting requirement is covered without switching between tools.
Corporate R&D teams working with technical reports, patents, and industry documents can use multi-document chat to query proprietary knowledge bases conversationally. The AI research assistant returns sourced answers tied to specific files rather than general knowledge — reducing hallucination risk and making outputs reliable for internal reporting and decision support.
Consultants and industry experts building client-specific knowledge bases can train Petal exclusively on their own document sets. Answers are grounded in those sources only. This makes the platform suitable for legal, regulatory, and advisory work where accuracy and source traceability are non-negotiable.
