CirrusPrint is designed to manage and streamline printing and document delivery across networks. It solves cloud migration problems related to printing, and provides the most direct and immediate method to deliver documents to your users. Traditional network printing works without changing operations, plus there are new capabilities: you can print to your users, or email your printers, or send a file from your phone to a printer across the country. CirrusPrint runs on Windows and Linux, in the cloud or your own data center. It accepts print jobs and other documents, parses and compresses them, and delivers them to remote printers or users. Integration with applications is simple and flexible: print to it like any network printer, email files to it, drop files into it, or use the REST API. Print jobs sent through CirrusPrint arrive quickly and securely at remote printers, as precise duplicates of the original print job.
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LM-Kit.NET is a complete local AI runtime for .NET that lets engineering teams ship AI-powered features without cloud dependencies, per-token costs, or data leaving the network.
Most .NET AI integrations stop at inference. LM-Kit.NET covers the full range of capabilities production applications actually need: agentic workflows with tool calling, planning, and memory; document intelligence with OCR and structured extraction; retrieval-augmented generation with built-in vector storage; multilingual speech-to-text; vision and multimodal understanding; text analysis with classification, NER, PII extraction, and sentiment; and text generation with translation, summarization, and constrained output.
Ships in one NuGet package, runs in-process with no sidecar services, and works across all major hardware acceleration backends. Drop-in replacement for Semantic Kernel through its Microsoft.Extensions.AI compatibility layer.
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Docling
Docling is an easy-to-use, self-contained, MIT-licensed open source toolkit for converting messy documents into structured data and simplifying downstream document and AI processing. It can parse many popular document formats into a unified and richly structured Docling Document, including PDF, DOCX, PPTX, XLSX, HTML, Markdown, AsciiDoc, CSV, images, audio, and scanned pages through an OCR engine of the user’s choice. Docling detects tables, formulas, reading order, chunks, bounding boxes, page headers and footers, pictures, captions, code, list items, paragraphs, cells, and document structure, making extracted content easier to process, search, and ingest into AI, RAG, and agentic systems. It can export parsed documents to JSON, text, Markdown, HTML, and Doctags, giving developers flexible outputs for pipelines and applications. Docling stores and traverses components according to reading order, partitions documents into bite-sized contiguous text chunks.
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