Square 9
The Square 9 AI-powered intelligent information processing platform takes the paper out of work and makes it easier to get things done with digital workflows that automate many aspects of how you work today. We make it easy by extracting information from scans or PDFs, storing documents in a searchable archive, and building digital twins of your current processes through graphical workflows.
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LM-Kit.NET
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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DeepTagger
DeepTagger is an innovative, no-code platform that utilizes artificial intelligence to transform various document types, such as PDFs, images, and Word files, into organized and actionable data using a user-friendly "highlight-and-label" system. Users simply upload their documents, select the relevant data points, and train the model through examples instead of relying on rigid templates, after which they can execute predictions, export their findings, and improve accuracy. The platform is designed to manage intricate structures, such as line items within invoices and tables within other tables, while also accommodating scanned documents and low-resolution images thanks to its powerful optical character recognition (OCR) capabilities. Additionally, DeepTagger includes functionalities for splitting multi-document PDFs, understanding intent and context, and position-aware extraction to differentiate repeated phrases for more precise data retrieval. Its pricing model is based on usage and offers a free tier for processing up to 200 documents, while higher subscription levels provide access to enhanced features, including batch prediction, nested schemas, priority support, a multi-tenant architecture, and compliance suitable for enterprise needs. Overall, DeepTagger stands out as a versatile solution for those looking to streamline their document processing and data extraction workflows.
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Airparser
Transform the way you handle data extraction with the innovative GPT parser, which enables the retrieval of structured information from various sources such as emails, PDFs, and other documents. This tool allows for real-time exporting of the extracted data to any application of your choice. Effortlessly gather signatures, contact details, dates, and important elements from human-generated emails and text messages. Additionally, you can convert handwritten notes, lists, and similar items into organized and actionable data formats. Capture important information like amounts, dates, ordered products, and vendor specifics from invoices, receipts, and purchase orders with precision. The tool also facilitates the automatic extraction of key components such as terms, parties involved, and essential details from contracts, making contract management considerably simpler. Furthermore, it smoothly collects vital information like names, contact numbers, and work history from CVs and resumes. Enhance your workflow by streamlining order processing through the extraction of order numbers, items, and delivery information from confirmation documents, ultimately boosting efficiency across various operations. By leveraging this powerful technology, users can significantly reduce manual data entry efforts and improve overall productivity.
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