Top Pick

LM-Kit.NET Description

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.

Pricing

Pricing Starts At:
Free (Community) or $1000/year
Pricing Information:
Free community license available
Free Version:
Yes
Free Trial:
Yes

Integrations

API:
Yes, LM-Kit.NET has an API

Reviews - 26 Verified Reviews

Total
ease
features
design
support

Company Details

Company:
LM-Kit
Year Founded:
2024
Headquarters:
France
Website:
Update This Listing

Media

Image Description with Local VLM

Image Description with Local VLM

Product Details

Platforms
Web-Based
Windows
Mac
Linux
iPhone App
iPad App
Android App
Chromebook
On-Premises
Types of Training
Training Docs
Live Training (Online)
Webinars
Training Videos
Customer Support
Online Support

LM-Kit.NET Features and Options

AI Agent Builders

LM-Kit.NET introduces sophisticated artificial intelligence capabilities for C# and VB.NET, featuring a robust enterprise architecture and a user-friendly AI Agent Builder. This tool empowers developers to create flexible agents for tasks such as text generation, translation, and context-sensitive decision-making. With integrated runtime support that simplifies the complexities of AI implementation, teams can rapidly prototype, deploy, and expand intelligent solutions, ensuring their software remains responsive to changing data and user requirements.

Data Extraction Software

LM-Kit.NET transforms unstructured text and image content into organized data tailored for your .NET applications. Its advanced extraction engine employs dynamic sampling techniques to accurately analyze various formats such as documents, emails, logs, and beyond. You can specify custom fields along with metadata and adaptable formats to suit your needs. Choose between the Parse method for synchronous processing or ParseAsync for asynchronous execution, accommodating any workflow requirements. Retrieval-Augmented Generation connects relevant segments for enhanced search capabilities. The entire process operates locally, ensuring quick performance, robust security, and complete data confidentiality—no registration required.

Disparate Data Collection
Document Extraction
Email Address Extraction
IP Address Extraction
Image Extraction
Phone Number Extraction
Pricing Extraction
Web Data Extraction

Conversational AI Platform

LM-Kit.NET empowers C# and VB.NET applications to integrate conversational AI using simplified APIs. It facilitates engaging multi-turn conversations and context-sensitive replies for chatbots, virtual assistants, and customer support agents, providing users with interactions that mimic human dialogue and adjust seamlessly in real-time.

Code-free Development
Contextual Guidance
For Developers
Intent Recognition
Multi-Languages
Omni-Channel
On-Screen Chats
Pre-configured Bot
Reusable Components
Sentiment Analysis
Speech Recognition
Speech Synthesis
Virtual Assistant

Natural Language Processing Software

The on-device NLP Toolkit designed for .NET efficiently handles extensive text data in a secure and instantaneous manner, ensuring that no information is transmitted to the cloud. Key functionalities encompass multilingual sentiment analysis, detection of emotions and sarcasm, personalized text classification, keyword extraction, and semantic embeddings that provide in-depth contextual understanding. Its dynamic sampling mechanism optimally utilizes both CPU and GPU capabilities to deliver enhanced speed and performance.

Co-Reference Resolution
In-Database Text Analytics
Named Entity Recognition
Natural Language Generation (NLG)
Open Source Integrations
Parsing
Part-of-Speech Tagging
Sentence Segmentation
Stemming/Lemmatization
Tokenization

Chatbot Software

This .NET chatbot library designed for on-device use introduces advanced multi-turn conversational AI that maintains context while ensuring quick response times and complete privacy. With lightweight models, it eliminates the need for cloud connectivity. You can customize the responses using techniques like RandomSampling or MirostatSampling, and manage token usage with LogitBias and RepetitionPenalty to achieve diverse and non-repetitive responses. Moreover, it features event-driven hooks that allow you to implement personalized logic before or after each message, as well as facilitating human-in-the-loop evaluations when necessary.

Call to Action
Context and Coherence
Human Takeover
Inline Media / Videos
Machine Learning
Natural Language Processing
Payment Integration
Prediction
Ready-made Templates
Reporting / Analytics
Sentiment Analysis
Social Media Integration

Natural Language Generation Software

The .NET-based on-device Natural Language Generation (NLG) module leverages streamlined local language models to efficiently produce contextually relevant text in a secure manner. It allows for the creation of code snippets, summaries, grammar corrections, and style enhancements directly within your system, ensuring that your data remains confidential. This tool is perfect for automating documentation, maintaining a consistent brand voice, and generating content in multiple languages. With its adaptable controls, you can specify various formats and styles, making it exceptionally suitable for tasks such as reporting, programming code creation, and generating succinct summaries.

Business Intelligence
CRM Data Analysis and Reports
Chatbot
Email Marketing
Financial Reporting
Multiple Language Support
SEO
Web Content

Sentiment Analysis Tool

The on-device sentiment analysis tool for .NET provides immediate and confidential insights. It categorizes text into positive, negative, or neutral sentiments, identifies emotions such as happiness, anger, sorrow, and fear, and recognizes sarcasm for more detailed evaluation. Transform unrefined text into valuable intelligence for customer support, social monitoring, marketing initiatives, and product development strategies.

Large Language Models

LM-Kit.NET empowers developers working with C# and VB.NET to seamlessly incorporate both extensive and compact language models for tasks such as natural language comprehension, text creation, engaging in multi-turn conversations, and facilitating rapid on-device inference. Additionally, its vision language models enhance functionality by providing image analysis and captioning capabilities. The embedding models transform text into vector representations, enabling swift semantic searches. Furthermore, the LM-Lit catalog offers a comprehensive list of cutting-edge models, continuously updated, all within a streamlined toolkit that integrates effortlessly into your codebase without disclosing any AI origins to the end user.

AI Development Platform

Developers can seamlessly integrate sophisticated generative AI capabilities into their .NET applications with minimal configuration. This enables functionalities such as chatbots, text creation, content discovery, natural language understanding, translation, and extracting structured information. The on-device inference leverages a combination of CPU and GPU acceleration for swift local processing, ensuring data security. Regular updates incorporate the latest advancements in research, allowing teams to create secure, high-performance AI solutions while enjoying an efficient development process and comprehensive oversight.

Generative AI Tool

LM-Kit.NET integrates generative AI capabilities into your .NET applications via a streamlined NuGet package. This powerful toolkit facilitates the creation of chatbots, text generation, content retrieval, natural language processing, translation, and function invocation, all with easy configuration. On-device inference is enhanced by a combination of CPU and GPU acceleration, ensuring rapid local processing and robust data protection. Regular updates ensure the toolkit remains aligned with the newest models, empowering developers to create high-performance, context-sensitive solutions that adapt to changing business requirements while maintaining the confidentiality of AI usage.

AI Agents

The AI agents component within LM-Kit.NET empowers developers to design, tailor, and implement agents for various applications such as text creation, translation, code evaluation, and more, all with minimal alterations to the existing codebase. A streamlined runtime and API framework facilitate seamless collaboration among multiple agents, enabling them to share information, allocate tasks, and execute simultaneously. Additionally, the option for on-device processing reduces delays and maintains data privacy, while extensive hardware compatibility ensures that these agents can operate effectively on laptops, edge devices, or cloud GPUs, optimizing performance, cost efficiency, and security.

AI Text Generators

The text generator from LM-Kit.NET operates on both CPU and GPU, enabling fast and secure content generation, summarization, grammar improvement, and style enhancement. With its dynamic sampling capabilities and adjustable grammar rules, it can produce organized outputs like JSON schemas, formatted documents, or code fragments that require minimal editing. Additionally, its efficient resource management ensures low latency and uniform results throughout various workflows.

AI Fine-Tuning Platform

LM-Kit.NET empowers .NET developers to enhance large language models using various parameters such as LoraAlpha, LoraRank, AdamAlpha, and AdamBeta1. It integrates efficient optimization techniques and dynamic sample batching to achieve quick convergence. The tool automates quantization, allowing models to be compressed into lower-precision formats, which accelerates inference on devices with limited resources while maintaining accuracy. Additionally, it facilitates the effortless merging of LoRA adapters, enabling the incorporation of new skills in just minutes, avoiding the need for complete retraining. With straightforward APIs, comprehensive guides, and support for on-device processing, LM-Kit.NET ensures a secure and user-friendly optimization process within your existing code framework.

Retrieval-Augmented Generation (RAG) Software

With LM-Kit RAG, you can implement context-aware search and provide answers in C# and VB.NET through a single NuGet installation, complemented by an instant free trial that requires no registration. Its hybrid approach combines keyword and vector retrieval, operating on your local CPU or GPU, ensuring only the most relevant data is sent to the language model, significantly reducing inaccuracies, while maintaining complete data integrity for privacy compliance. The RagEngine manages various modular components: the DataSource integrates documents and web pages, TextChunking divides files into overlapping segments, and the Embedder transforms these segments into vectors for rapid similarity searching. The system supports both synchronous and asynchronous workflows, capable of scaling to handle millions of documents and refreshing indexes in real-time. Leverage RAG to enhance knowledge chatbots, enterprise search capabilities, legal document review, and research assistance. Adjusting chunk sizes, metadata tags, and embedding models allows you to optimize the balance between recall and speed, while on-device processing ensures predictable expenses and safeguards against data leakage.

AI Inference Platform

LM-Kit.NET integrates cutting-edge artificial intelligence into C# and VB.NET, enabling you to design and implement context-sensitive agents that execute compact language models on edge devices. This approach reduces latency, enhances data security, and ensures immediate performance, even in environments with limited resources. As a result, both enterprise-level solutions and quick prototypes can be developed and launched more efficiently, intelligently, and dependably.

AI Models

LM-Kit.NET now empowers your .NET applications to operate the most recent open models directly on your device. This includes advanced models such as Meta Llama 4, DeepSeek V3-0324, Microsoft Phi 4 (along with its mini and multimodal versions), Mistral Mixtral 8x22B, Google Gemma 3, and Alibaba Qwen 2.5 VL. By doing this, you can achieve state-of-the-art capabilities in language processing, vision, and audio without relying on any external services. For easy integration of new models, a regularly updated catalog complete with setup guides and quantized versions is accessible at docs.lm-kit.com/lm-kit-net/guides/getting-started/model-catalog.html. This ensures that you can quickly adopt the latest releases while maintaining low latency and ensuring the complete privacy of your data.

LM-Kit.NET Lists

  • Name: Dexter T.
    Job Title: Developer
    Length of product use: Less than 6 months
    Used How Often?: Daily
    Role: User, Administrator, Deployment
    Organization Size: 1 - 25
    Features
    Design
    Ease
    Pricing
    Support
    Likelihood to Recommend to Others
    1 2 3 4 5 6 7 8 9 10

    Very light weight and developer friendly

    Date: Apr 29 2026

    Summary: LM-Kit is a solid step toward making LLM integration cleaner and more maintainable in .NET applications. If you’re building AI-enabled .NET apps and value clean architecture, LM-Kit is worth exploring.

    Positive: 1. Clean and Developer-Friendly API
    The library follows familiar .NET patterns, making it easy to adopt. Dependency injection support and clear interfaces reduces the time in getting started.

    2. Abstraction Over Multiple Providers
    LM-Kit doesn’t tie you to a single LLM provider. This flexibility is valuable if you want to switch vendors or support multiple backends without rewriting your core logic.

    3. Prompt Management
    It provides structured ways to manage prompts, which helps avoid scattered string literals across your codebase. This becomes especially useful in larger projects.

    Negative: Being relatively new, it doesn’t yet have a large ecosystem or community backing. This means fewer tutorials, plugins, and third-party integrations. But it's ok. I was able to use the documentation to get through.

    Read More...
  • Name: Sumo S.
    Job Title: Sr. AWS Analyst
    Length of product use: Free Trial
    Used How Often?: Weekly
    Role: User, Administrator
    Organization Size: 100 - 499
    Features
    Design
    Ease
    Pricing
    Support
    Likelihood to Recommend to Others
    1 2 3 4 5 6 7 8 9 10

    LM-Kit performs better than Ollama

    Date: Apr 13 2026

    Summary: So I got a community license key from the support team and added this kit through Nuget to my project. With just one line of code I had it returning AI responses for my project. Pretty smart if you ask me.

    I have only tried building my own chat bot with this tool but can confirm that it works flawlessly for local LLM projects.

    Positive: Quick integration and faster responses compared to Ollama. I have used almost every other local tool but none oofer .net integration capabilities like this tool, or any other local usage method such as port integration or file importing and merging.

    Another good feature is that I can train models locally with my own data.

    Also the community license is free forever and can be shipped with your products with a reference the tool. Pretty good offer.

    Negative: None worth mentioning. Although they could add a loader when importing large LLM models like GPT OSS 120B.

    Read More...
  • Name: Jacub F.
    Job Title: Sr. Technical Developer
    Length of product use: Less than 6 months
    Used How Often?: Daily
    Role: User, Administrator, Deployment
    Organization Size: 100 - 499
    Features
    Design
    Ease
    Pricing
    Support
    Likelihood to Recommend to Others
    1 2 3 4 5 6 7 8 9 10

    Hands down the best agentic .net package in the market

    Date: Mar 13 2026

    Summary: Used it for like 2days. Downloaded it, got a free license in my email from the team. Downloaded mistral 3b AI model from huggingface. Loaded it and started chatting on technical issues. Works like a charm. Although please be advised that using models without a powerful GPU will be very slow to generate responses.

    Positive: This SDK is so amazing. Got started within like 15 minutes of downloading it from nuget. Some of the features are really out of this world :
    1) RAG pipeline - You can literally build your own data searching functions across the entire web using this.
    2) Finetuning and Quantization both are available built in this package. I have built my own custom legal finetuned models available in Q6 and Q4 4 bits and 2bits (like literally custom functions which you can just run).
    3) LORA adapters are also available in LM-Kit. You just have to prepare your own data and add it to this kit.
    4) Load any publically available model from huggingface such as Mistral, Gemma, Phi etc. Works off the bat.

    So much available for so less. These people are seriously very hard working and provide amazing support for free (have answered all my questions in support email).

    Negative: not much till now. I guess it can warn about memory requirements before the model is loaded or show some loading message.

    Read More...
  • Name: Nahuel R.
    Job Title: Software Engineer
    Length of product use: Free Trial
    Used How Often?: Daily
    Role: User, Administrator, Deployment
    Organization Size: 1 - 25
    Features
    Design
    Ease
    Pricing
    Support
    Likelihood to Recommend to Others
    1 2 3 4 5 6 7 8 9 10

    Great SDK for working with LLMs and RAG in .NET

    Date: Feb 15 2026

    Summary: No real complaints on the documentation and API side, everything was super easy to set up. My preferred language is C# so it was neat to find a framework that runs locally, provides RAG and everything I need to set up my project in a language and framework I'm familiar with.

    Positive: Fully local solution, with great integration with .NET. The API is very easy to use and samples are thorough, made RAG very easy to integrate into my project, plus a free community license!

    Negative: My only complaint currently is that it's a pretty small ecosystem as it's a new solution, but I'm expecting that to improve rapidly.

    Read More...
  • Name: Zaid S.
    Job Title: Developer
    Length of product use: Less than 6 months
    Used How Often?: Daily
    Role: Administrator
    Organization Size: 1 - 25
    Features
    Design
    Ease
    Pricing
    Support
    Likelihood to Recommend to Others
    1 2 3 4 5 6 7 8 9 10

    Easy to use and understand

    Date: Dec 03 2025

    Summary: LM-Kit.NET is compelling if you are a .NET developer (C# / VB.NET) looking to embed generative-AI capabilities locally, privately, and at scale, without relying on external cloud APIs. It’s especially suited for startups, internal tools, applications with privacy or compliance requirements, or environments where latency and data sovereignty matter.

    If your needs are small, sporadic, or in a different tech stack, the extra overhead of maintaining hardware and models may outweigh its benefits.

    In short: LM-Kit.NET is a powerful, mature, “local-first” AI SDK that gives you freedom, control, and performance — but it demands responsibility, some work, and potentially hardware investment if you go beyond minimal use.

    Positive: Local / on-device inference & data privacy: LM-Kit.NET runs models entirely on your hardware (CPU/GPU/NPU). That means no data leaves your environment — ideal if privacy, compliance or sensitive data handling matters.
    Performance and low latency: Because inference is local, response times tend to be fast and predictable. The framework is optimized for performance across different hardware (CPU, GPU, Apple Silicon, etc.).

    Negative: More setup & maintenance overhead: Since you’re managing models and hardware yourself, there’s more responsibility — provisioning hardware, ensuring compatibility, model updates, etc.
    You have to manage and source models (or opt for paid models): While LM-Kit.NET supports open-source models (GGUF etc.), if you need pre-trained models maintained by LM-Kit or want “proprietary” models, that may require licenses / commercial agreement.

    Read More...
  • Name: Anonymous (Verified)
    Job Title: Developer
    Length of product use: Free Trial
    Used How Often?: Daily
    Role: Administrator
    Organization Size: 26 - 99
    Features
    Design
    Ease
    Pricing
    Support
    Likelihood to Recommend to Others
    1 2 3 4 5 6 7 8 9 10

    Amaizing LM-Kit.NET

    Date: Oct 14 2025

    Summary: Accelerated Image Processing on Android due to Vulkan on Maui Applications. Accurate and simple to implement Image Similarity Search.

    Positive: No need to use Python when developing .NET applications that use LLM.
    Very easy to use. Fast deployment. Samples that include most of the AI tasks.

    Negative: Missing LM-Kit Cloud hosting with GPU.
    Missing Meta Sam and Dinov3 models.

    Read More...
  • Name: Iván C.
    Job Title: Professor
    Length of product use: Free Trial
    Used How Often?: Daily
    Role: User
    Organization Size: 1 - 25
    Features
    Design
    Ease
    Pricing
    Support
    Likelihood to Recommend to Others
    1 2 3 4 5 6 7 8 9 10

    The best software for AI

    Date: Oct 09 2025

    Summary: Great

    Positive: This software is ideal for build AI models of all architectures in short time with a excellent quality of responses.

    Negative: Nothing, this program is ideal in the actual state.

    Read More...
  • Name: Anonymous (Verified)
    Job Title: User
    Length of product use: 6-12 Months
    Used How Often?: Monthly
    Role: User, Administrator, Deployment
    Organization Size: 1 - 25
    Features
    Design
    Ease
    Pricing
    Support
    Likelihood to Recommend to Others
    1 2 3 4 5 6 7 8 9 10

    Using LM-Kit

    Date: Oct 08 2025

    Summary: Very good and useful, integrated well for my existing project work and was a great experience overall.

    Positive: The ability to build AI functionality into Windows Forms applications by using it as a NuGet package.

    Negative: Can only run on PCs with Intel chips, otherwise I get an exception when attempting to run the application’s AI functionality on ARM chips.

    Read More...
  • Name: Anurak S.
    Job Title: CTO
    Length of product use: 6-12 Months
    Used How Often?: Daily
    Role: User
    Organization Size: 26 - 99
    Features
    Design
    Ease
    Pricing
    Support
    Likelihood to Recommend to Others
    1 2 3 4 5 6 7 8 9 10

    Best .NET SDK for Advanced RAG & AI Workflows

    Date: Sep 07 2025

    Summary: LM-Kit.NET is unique in the .NET ecosystem and has no real equivalent. I needed a fully local solution for my company and this SDK delivered exactly that. It made building a complex RAG system with advanced extraction and classification both possible and efficient. For anyone serious about Generative AI in .NET, this is the tool to use. New features are added frequently, and I can’t wait to see what’s next.

    Thanks for this great product!

    Positive: 100% local solution
    Advanced RAG, extraction, and classification capabilities
    Developer friendly, very easy integration in .NET
    Highest accuracy level that I found on the market, very coherent results
    Free community license to get started

    Negative: Documentation could include more enterprise-level examples
    Ecosystem and community is small but I understand the product is new

    Read More...
  • Name: Anonymous (Verified)
    Job Title: Sr software engineer
    Length of product use: Free Trial
    Used How Often?: Daily
    Role: User
    Organization Size: 100 - 499
    Features
    Design
    Ease
    Pricing
    Support
    Likelihood to Recommend to Others
    1 2 3 4 5 6 7 8 9 10

    Excellent

    Edited: Aug 25 2025

    Summary: Excellent performance I like this kit its very useful for starting development with Gen AI and Agentic AI

    Positive: Microsoft phi model I like as a dot net developer point of view. I would recommend everyone. Net developer should use it

    Negative: First time it takes time but after that it's working fine

    Read More...
  • Name: Anonymous (Verified)
    Job Title: Software Developer
    Length of product use: Less than 6 months
    Used How Often?: Daily
    Role: Deployment
    Organization Size: 1 - 25
    Features
    Design
    Ease
    Pricing
    Support
    Likelihood to Recommend to Others
    1 2 3 4 5 6 7 8 9 10

    Very useful and helpful

    Date: Jul 19 2025

    Summary: It was very helpful and easy to use and helpful with my application and reduce development time of all developer

    Positive: Integrating It with .Net applications which helped developer with many things. For me it helped in summarising text which is extracted through ocr

    Negative: Till now i have not found any cons because everything is available in documents

    Read More...
  • Name: Ulisses R.
    Job Title: Developer
    Length of product use: Free Trial
    Used How Often?: Weekly
    Role: Deployment
    Organization Size: 1 - 25
    Features
    Design
    Ease
    Pricing
    Support
    Likelihood to Recommend to Others
    1 2 3 4 5 6 7 8 9 10

    An inspiring surprise

    Date: Jun 19 2025

    Summary: The tool has a great future and could become a reference among libraries that allow the use of artificial intelligence.

    Positive: The tool allows you to quickly create an application that can access multiple platforms and artificial intelligence models.

    Negative: I found the price a bit high for independent developers. They could review their pricing policy.

    Read More...
  • Name: Maria L.
    Job Title: Developer
    Length of product use: Free Trial
    Used How Often?: Weekly
    Role: Deployment
    Organization Size: 1 - 25
    Features
    Design
    Ease
    Pricing
    Support
    Likelihood to Recommend to Others
    1 2 3 4 5 6 7 8 9 10

    Incredible!

    Date: Jun 10 2025

    Summary: Good documentation, good features and very practical. Congratulations on the initiative, team! I'm loving it!

    Positive: Developers in the .NET environment needed a tool like this, which would be able to centralize all artificial intelligence functionalities.

    Negative: I found the price a bit high for indie developers. Please review.

    Read More...
  • Name: Marina P.
    Job Title: Developer
    Length of product use: Free Trial
    Used How Often?: Weekly
    Role: User
    Organization Size: 1 - 25
    Features
    Design
    Ease
    Pricing
    Support
    Likelihood to Recommend to Others
    1 2 3 4 5 6 7 8 9 10

    Great choice!

    Date: Jun 10 2025

    Summary: One of the best tools I've discovered in recent times. It will help a lot! Very easy to use! Highly recommended.

    Positive: Lots of amazing features to make it easier to use artificial intelligence in your products! It can be used in multiple versions of .NET.

    Negative: For indie developers the price may be a bit high. The community version may not be sufficient for some.

    Read More...
  • Name: Ulisses C.
    Job Title: Developer
    Length of product use: Free Trial
    Used How Often?: Daily
    Role: User, Administrator, Deployment
    Organization Size: 1 - 25
    Features
    Design
    Ease
    Pricing
    Support
    Likelihood to Recommend to Others
    1 2 3 4 5 6 7 8 9 10

    Innovative product

    Date: Jun 07 2025

    Summary: The library is fantastic, with many features. It makes it easy to integrate different models. I recommend it.

    Positive: The product stands out for its innovation in the .NET ecosystem, making it easier for developers to use artificial intelligence.

    Negative: The pricing policy could be adapted to suit indie developers. There is a community version, but it could have an intermediate plan.

    Read More...
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