Foxit delivers a robust set of cloud-native APIs that enable organizations to automate and modernize document-driven workflows at scale. Built on flexible REST architecture, these APIs allow developers to seamlessly create, convert, extract, sign, and display documents within their own applications—improving efficiency while reducing manual processes.
The Foxit PDF Services API handles large-scale PDF processing, including conversion, extraction, optimization, and redaction. The Document Generation API streamlines the production of personalized PDFs and DOCX files using dynamic templates and live business data. The Foxit eSign API integrates secure, legally binding eSignature workflows with audit tracking and compliance capabilities. The PDF Embed API provides customizable in-app document viewing with support for annotations, forms, and secure user access.
Combined, Foxit APIs give enterprises a secure and scalable platform for digital document automation and workflow transformation.
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LM-Kit.NET is an enterprise-grade toolkit designed for seamlessly integrating generative AI into your .NET applications, fully supporting Windows, Linux, and macOS. Empower your C# and VB.NET projects with a flexible platform that simplifies the creation and orchestration of dynamic AI agents.
Leverage efficient Small Language Models for on‑device inference, reducing computational load, minimizing latency, and enhancing security by processing data locally. Experience the power of Retrieval‑Augmented Generation (RAG) to boost accuracy and relevance, while advanced AI agents simplify complex workflows and accelerate development.
Native SDKs ensure smooth integration and high performance across diverse platforms. With robust support for custom AI agent development and multi‑agent orchestration, LM‑Kit.NET streamlines prototyping, deployment, and scalability—enabling you to build smarter, faster, and more secure solutions trusted by professionals worldwide.
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Docling
Docling is a user-friendly, self-sufficient, open-source toolkit licensed under MIT that facilitates the transformation of disorganized documents into structured data, thereby enhancing subsequent document and AI workflows. This versatile tool can interpret a wide array of document types, including PDF, DOCX, PPTX, XLSX, HTML, Markdown, AsciiDoc, CSV, images, audio files, and even scanned documents using any preferred OCR engine. Docling proficiently identifies and processes various elements such as tables, formulas, reading sequences, bounding boxes, headers, footers, images, captions, code snippets, list items, paragraphs, and overall document architecture, which significantly aids in the searchability and integration of the extracted content into AI systems, retrieval-augmented generation, and agent-based applications. Furthermore, it allows for exporting the parsed output in formats like JSON, plain text, Markdown, HTML, and Doctags, thus providing developers with versatile options for their development pipelines and applications. By efficiently organizing and managing components based on reading sequence, Docling breaks down documents into manageable, continuous text segments, optimizing the processing experience.
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PrecisionOCR
PrecisionOCR is an easy-to-use, secure and HIPAA-compliant cloud-based optical character recognition (OCR) platform that organizations and providers can user to extract medical meaning from unstructured health care documents.
Our OCR tooling leverages machine learning (ML) and natural language processing (NLP) to power semi-automatic and automated transformations of source material, such as pdfs and images, into structured data records. These records integrate seamlessly with EMR data using the HL7s FHIR standards to make the data searchable and centralized alongside other patient health information.
Our health OCR technology can be accessed directly in a simple web-UI or the tooling can be used via integrations with API and CLI support on our open healthcare platform.
We partner directly with PrecisionOCR customers to build and maintain custom OCR report extractors, which intelligently look for the most critical health data points in your health documents to cut through the noise that comes with pages of health information.
PrecisionOCR is also the only self-service capable health OCR tool, allowing teams to easily test the technology for their task workflows.
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