Turn your paper into figures,
page by page.

Yes. Your unpublished draft stays yours, full stop.

• Zero AI Training: Uploaded PDFs are read only to build your generation prompt. Never recycled into model training — ever.
• Draft-Safe by Default: Pre-publication manuscripts, confidential grant drafts, embargoed data — all treated identically to any other upload. No exceptions.
• Yours to Delete: Delete an uploaded PDF at any time and the stored file is removed from our storage, not just hidden from your view.

Drop the manuscript. SciFig PDF to figure reads it. You get a graphic abstract.

• Manuscript In, Visual Out: Don't stare at a blank canvas after 40 pages of writing. Upload your draft PDF — the LLM reads the paper and drafts a generation prompt, producing a single-panel graphic abstract in minutes.
• Your Angle, Your Prompt: The manuscript sets the science; your prompt sets the emphasis. Add a line like "focus on the core mechanism, not the assay controls" and regenerate until the angle is yours.
• Journal-Ready on Demand: Output is high-res raster by default. One-click vectorize to SVG/PPTX when your target journal asks for editable layers.

Your abstract is enough. A poster comes out of it.

• Abstract-First Workflow: Paste your abstract as a PDF and SciFig PDF to figure reads the text, drafting the poster's visual scaffolding around the headline finding.
• No Printing-Night Panic: Generate a draft poster in minutes instead of the night-before-the-conference scramble. Regenerate any section without rebuilding the whole layout.
• Polish Where It Counts: Vectorize to PPTX when you need to hand-tweak titles, affiliations, and QR codes in PowerPoint before the print-shop cutoff.

Point SciFig at Methods only. Get just the diagram.

• Section-Selective Focus: You don't have to feed the whole paper. Upload your PDF and tell SciFig to read just the Methods section — intro, results, and discussion are ignored when the prompt is drafted.
• Order Preserved: A linear workflow, a branching protocol, a multi-plate assay — whatever your Methods describes, the generated diagram keeps the step order intact.

Grant draft in, roadmap out. Deadline intact.

• Proposal-Aware Reading: Upload your proposal draft or LOI. SciFig reads Specific Aims, Research Plan, and timeline language, then drafts a visual roadmap showing aims, dependencies, and milestones.
• Your Terminology, Same Figure: Call it a "research roadmap," "technical roadmap," or "Specific Aims figure" — the generated diagram covers the same job. Tune axes, swim-lanes, or phase colors with an added prompt.
• Revise Per Reviewer Pass: Reviewer wants a clearer Aim 3? Regenerate just that panel instead of the whole figure. Keeps your resubmission deadline intact.

Any paper in your reading list becomes a talk-ready infographic.

• Reading-List Friendly: Upload a paper you're reviewing or referencing — the LLM distills the core finding into a plain-language prompt, then draws a new infographic from that prompt.
• Talk, Classroom, Science-Comm: Same flow for conference talks, lab meetings, teaching slides, and popular-science articles. The output is a fresh visual built from the summary — no figure lifting from the source.
• One-Step Attribution: Put "include an attribution line 'Adapted from [Author, Year]'" into your prompt and SciFig renders the citation directly in the figure — no post-generation canvas edit needed.

One PDF, many scientific figures. SciFig PDF to figure runs one section at a time.

• Section-Selective Focus: Tell SciFig which section to read — Methods, Results, Discussion, Specific Aims, even a single paragraph. The LLM ignores the rest when drafting the prompt.
• Full Figure Set From One Upload: Run the same PDF with different section targets to populate the lineup — graphic abstract from the abstract, method diagram from Methods, workflow from Results, roadmap from Aims.

Upload supplies the science. Your prompt supplies the angle.

• PDF Is the Content: Whatever's in the paper — mechanisms, data, methods — is what the LLM reads when drafting the generation prompt. You don't retype the science.
• Your Prompt Is the Steering: Add a single line to focus the output: "emphasize the kinase cascade, not the downstream effects," "two-column layout, editorial palette," "omit the statistics panel." Without steering, you get SciFig's default interpretation.

One PDF per generation — that's the current limit.

• Single-File Focus: One PDF at a time keeps the LLM tightly focused on a single document's content.
• Run It Again: Upload a different PDF on each generation — all results stay grouped in one project for easy comparison.
• Synthesizing Multiple Sources: Need one figure that pulls from several papers? Summarize the key points yourself first, then use Text-to-Figure to generate from the summary.

20 MB per file. No page cap. No OCR setup on your end.

• Up to 20 MB per PDF: Covers almost every journal article, including figure-heavy papers. (Note: For 100 MB+ textbooks, split by chapter first.)
• No Page Limit: Long reviews, theses, textbook chapters — the LLM reads end-to-end instead of truncating at page N.
• OCR-Adaptive: Scanned PDFs from the 1990s and digital-native exports both work. You don't have to run OCR yourself — the LLM reads whatever is parseable.

SciFig PDF to figure exports raster for most journals and vector for element-level edits.

• Raster Is the Default Output: PNG/JPG up to 8K — clears 300 DPI at standard journal column widths. Enough for the large majority of submissions, talks, and posters.
• Vectorize for Layered Editing: One click converts the figure to SVG/PPTX. Every shape becomes a separately selectable object in Illustrator, Inkscape, Figma, or PowerPoint.

Three paths. Pick whichever is fastest for your fix.

• Inline Text Edit: Click the label and retype it — no regeneration needed for typos, wrong gene names, or mislabeled proteins.
• Reprompt the Section: For a wrong structure or a missing element, tighten the prompt ("the kinase is JAK2, not JAK1") and regenerate. Fastest for anything the LLM misinterpreted from the source.
• Vectorize for Surgical Edits: Need to move an arrow, recolor one panel, or swap one icon? Vectorize first, then edit the specific shape — everything else stays intact.