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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Nutrient provides an extensive solution for all your PDF requirements, delivering tools that seamlessly operate PDF features across any platform.
1. SDK: Incorporate advanced PDF functionality into iOS, Android, Windows, web, or any cross-platform technology, supplying abilities like PDF viewing, annotation, collaboration, and beyond.
2. Libraries: Employ our powerful .NET and Java libraries to enhance your backend applications with batch processing of redactions and PDF forms, OCR'd scanned text, and PDF document editing, all directly from your application server.
3. Processor: Our agile PDF microservice, Processor, enables rapid generation of PDFs from HTML, including HTML forms, as well as Office-to-PDF conversions, OCR, redaction, and XFDF combining and exporting.
4. PDF API: Take advantage of our hosted PDF API to generate, convert, and alter PDF documents in your workflows. We handle the development and server management, freeing you up to concentrate on your business.
At Nutrient, we're not just a tool; we're a committed ally in your success. Gain direct contact with our engineers for expert guidance, utilize comprehensive examples to simplify integration, and make the most of our top-tier documentation.
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Box Extract
Box Extract is an innovative data extraction tool powered by AI, designed to effectively pinpoint, gather, and transform structured data from unstructured sources, including documents, PDFs, spreadsheets, images, and various file formats into organized metadata that can be easily stored, searched, and utilized for streamlining business operations. This solution integrates advanced large language models, optical character recognition (OCR), chain-of-thought prompting, specialized retrieval-augmented generation, and reasoning techniques to achieve a deep understanding of document content and format with exceptional precision, all without the need for extensive model training or complicated configurations. Users have the option to select either Standard or Enhanced Extract Agents, which can manage everything from straightforward fields such as names and dates to intricate elements like risky clauses, tables, and graphs. Additionally, they can create Custom Extract Agents using configurable metadata templates, enabling large-scale operations across various folders and repositories. This flexibility ensures that businesses can tailor the solution to their specific needs, maximizing efficiency and effectiveness in data handling.
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Vellparser
Vellparser is an advanced AI-driven solution designed to extract data from disorganized PDFs, scanned documents, images, invoices, and forms, transforming them into neatly organized structured data. You can specify the necessary fields, tables, and details, then simply upload your documents to receive reliable outputs that can be exported to formats such as JSON, CSV, Excel, and more for use in databases or automated workflows. This tool empowers teams to eliminate tedious copy-and-paste tasks by offering a streamlined, no-code extraction process that can be easily replicated whenever needed. By utilizing Vellparser, organizations can enhance efficiency and accuracy in their data handling practices.
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