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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Enterprise Bot, based in Switzerland, is a pioneer in Conversational AI, Process Automation, and Generative AI. With the trust of esteemed enterprise giants across industries like Generali, SIX, SBB, DHL, and SWICA, Enterprise Bot is revolutionizing both customer and employee experiences. Through its advanced integration with Large Language Models (LLM) such as ChatGPT and Llama 2, and its unique patent-pending DocBrain technology, the company delivers unparalleled personalization, active engagement, and omnichannel solutions across platforms like email, voice, and chat. Furthermore, Enterprise Bot integrates with existing core systems, such as SAP, CRMs, Confluence and more, and with its proprietary middleware, Blitzico, enables the AI to not only respond to queries but also take action to resolve them. This dedication to innovation in four main use case areas, Customer Support, Sales and Marketing, Knowledge Management and Digital Coworker, elevates both CX and employee productivity.
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spaCy
spaCy is designed to help you do real work, build real products, or gather real insights. The library respects your time and tries to avoid wasting it. It's easy to install, and its API is simple and productive. spaCy excels at large-scale information extraction tasks. It's written from the ground up in carefully memory-managed Cython. If your application needs to process entire web dumps, spaCy is the library you want to be using. Since its release in 2015, spaCy has become an industry standard with a huge ecosystem. Choose from a variety of plugins, integrate with your machine learning stack, and build custom components and workflows. Components for named entity recognition, part-of-speech tagging, dependency parsing, sentence segmentation, text classification, lemmatization, morphological analysis, entity linking, and more. Easily extensible with custom components and attributes. Easy model packaging, deployment, and workflow management.
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