Apryse (formerly PDFTron) powers the future of document technology.
We help businesses, developers, and enterprises handle documents with unmatched speed, accuracy, and security. Whether running in secure server environments or delivering seamless web-based experiences, Apryse makes document workflows smarter and easier.
With Apryse, you can:
Embed powerful document features directly into your apps — from viewing and editing to collaboration and compliance.
Run at enterprise scale on secure server infrastructure, ensuring reliability without cloud dependencies.
Deliver seamless in-browser document experiences with responsive, accessible, and feature-rich web capabilities.
Trusted globally, Apryse empowers organizations to simplify operations, enhance productivity, and create exceptional document experiences.
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Adobe Acrobat Studio is a leading enterprise document platform built to scale for global teams — delivering AI-powered document intelligence, trusted PDF tools, and on-brand content creation in one secure solution.
Core capabilities include PDF creation, editing, conversion, annotation, redaction, e-signatures, and fillable forms. AI Assistant enables conversational document intelligence across PDFs, Word docs, spreadsheets, and more — surfacing summaries, key insights, and source-linked citations for verified, audit-ready answers. PDF Spaces organizes files, collaboration, and context into centralized knowledge hubs. The Generate Presentation feature transforms any document into a polished, branded deck using AI and Adobe Express templates.
Enterprise-grade encryption, admin controls, and compliance workflows support secure document sharing and high-volume document processing at scale — across Legal, Finance, HR, Sales, and more. Available on desktop, web, and mobile.
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Swivl
swivl is simplifying AI training.
In general, data scientists typically spend 80% of their time on non-value-added tasks such as finding, cleaning, and annotating data.
Our no-code SaaS platform helps teams outsource these data annotation tasks to a vetted network of data annotators to close the feedback loop in a cost-effective way. This involves the action of training, testing, and deploying machine learning models with an emphasis on natural language processing, audio, and generalized data categorization.
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