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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Improve radiology reporting efficiency and report quality with Imorgon's reporting automation.
As the top DICOM SR software for radiology, our solution significantly reduces unnecessary dictation by precisely transferring ultrasound and DEXA modality measurements into Powerscribe, Fluency, or RadAI. This eliminates manual errors and significantly accelerates the generation of reports.
Imorgon's unique advantages include:
- guaranteed transfer of all measurements - usually DICOM SR
- electronic worksheets for direct report population (eliminating dictation from notes)
- worksheets with priors, calculators, and clinical decision support (TI-RADS, O-RADS, etc)
- integration with Epic and other EHRs.
- vendor-neutral
Our dedicated support team ensures uninterrupted workflow.
Invest in Imorgon for a quick and substantial return on investment, transforming your reporting overhead into a streamlined, high-quality operation.
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GigaChat
GigaChat is adept at addressing user inquiries, engaging in conversations, generating program code, and producing written content and images based on provided descriptions, all within a cohesive framework. In contrast to other neural networks, GigaChat is designed from the ground up to facilitate multimodal interactions and demonstrates superior proficiency in the Russian language.
The foundation of GigaChat lies in the NeONKA (NEural Omnimodal Network with Knowledge-Awareness) model, which consists of a diverse array of neural network systems and employs techniques such as supervised fine-tuning and reinforcement learning enhanced by human feedback. As a result, Sber's innovative neural network is capable of tackling a variety of cognitive challenges, including maintaining engaging dialogues, generating informative texts, and answering factual queries. Moreover, the integration of the Kandinsky 2.1 model within this ensemble enhances its capabilities, enabling the creation of intricate images based on user prompts, thereby expanding the potential applications of the service. This multifaceted functionality positions GigaChat as a versatile tool in the realm of artificial intelligence.
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Nemotron 3 Super
The Nemotron-3 Super is an innovative member of NVIDIA's Nemotron 3 series of open models, specifically crafted to facilitate sophisticated agentic AI systems that can effectively reason, plan, and carry out multi-step workflows in intricate environments. This model features a unique hybrid Mamba-Transformer Mixture-of-Experts architecture that merges the streamlined efficiency of Mamba layers with the contextual depth provided by transformer attention mechanisms, which allows it to adeptly manage extended sequences and intricate reasoning tasks with impressive accuracy and throughput. By activating only a portion of its parameters for each token, this architecture significantly enhances computational efficiency while preserving robust reasoning capabilities, making it ideal for scalable inference under heavy workloads. The Nemotron-3 Super comprises approximately 120 billion parameters, with around 12 billion being active during inference, which substantially boosts its ability to handle multi-step reasoning and collaborative interactions among agents within extensive contexts. Such advancements make it a powerful tool for tackling diverse challenges in AI applications.
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