On-Device AI Agent Platform for .NET Developers
Your AI. Your Data. On Your Device.
Full-stack AI application framework: 100% local
LM-Kit gives you everything you need to build and deploy AI agents with zero cloud dependency. It unifies trained models, on-device inference, orchestration, RAG pipelines, MCP-compatible tool calling, and reusable task specialists in a single framework. Built for .NET developers who need complete data sovereignty and no external API calls.
Trained Models
Domain-tuned, compact models ready for production.
Inference Engine
Fast, private, on-device execution across CPU, GPU, and NPU.
Task Agents
Reusable specialists for repeatable, high-accuracy tasks.
Orchestration
Compose workflows with RAG, tools, and APIs under strict control.
Workflow Re-Invention with integrated Gen-AI
Not every problem requires a massive LLM to be solved!
LM-Kit eliminates the need for oversized, slow, and expensive cloud models by introducing dedicated tasked agents. These agents are designed to excel at specific tasks with greater speed and accuracy, and can be orchestrated into full workflows that go beyond isolated automation.
Obtain faster execution, lower costs and tangible business impact, with complete data control, no cloud subscription dependency and minimal resource usage. 
Optimized Execution
Faster performance with agents specialized for specific tasks
Cost Efficiency
Reduce infrastructure and cloud expenses with lightweight specialized models
Data Sovereignty
Keep sensitive information fully under your control
Resource Efficiency
Achieve high accuracy with minimal hardware usage
Executing Gen-AI with Native SDKs
Seamless Integration, Optimized Performance
LM-Kit specializes in providing native SDKs, delivering seamless AI integration with your existing applications.
By optimizing for each platform, native SDKs enhance performance, reduce latency, and
improve resource management, all while leveraging hardware capabilities for efficient AI operations.
This approach simplifies development by letting you use familiar tools and languages,
minimizing the learning curve and accelerating deployment.
The complete framework for building local AI agents
Q&A: Provide answers to queries with both single and multi-turn interactions.
Text Generation: Create relevant text automatically.
Constrained Generation: Generate text within constraints using JSON schema, grammar rules, templates, or other methods to enforce structure.
Text Correction: Correct spelling and grammar.
Text Rewriting: Rewrite text with a specific style.
Text Translation: Seamlessly convert text between languages.
Language Detection: Accurately identify the language from text, image, or audio input.
Text Summarization: Generate concise and accurate summaries from lengthy text.
Text Quality Evaluation: Evaluate content quality metrics.
Smart Memory: Enrich agent responses by integrating external knowledge or past interaction context.
Retrieval-Augmented Generation (RAG): Supports multimodal RAG by retrieving and integrating relevant external information to enhance the quality and context of generated outputs.
Tool Calling & Agent Orchestration: Enable AI agents to dynamically invoke external tools and functions through structured schemas, with built-in safety policies and human-in-the-loop controls for reliable agentic workflows
Model Context Protocol (MCP) Support: Connect agents to standardized data sources and tools through MCP servers, enabling seamless integration with external systems while maintaining full local execution.
Multimodal Embeddings & Reranking: Convert text and images into numerical representations that capture meaning, and leverage these embeddings to rerank results for improved relevance.
Vector Database Integration: Use a built-in engine for full autonomy, or connect to external databases like Qdrant.
Structured Data Extraction: Accurately extract and structure data from any source using customizable extraction schemes.
Schema Discovery: Automatically discover and generate extraction schemas from sample documents to accelerate development.
Custom Classification: Categorize text into predefined classes.
Sentiment Analysis: Detect the emotional tone in text.
Emotion Detection: Identify specific emotions in text.
Sarcasm Detection: Detect sarcasm in written text.
Keyword Extraction: Extract essential keywords from large text.
Named Entity Recognition (NER): Extract key entities from text or images.
PII Extraction: Identify and classify personal identifiers (names, addresses, phone numbers, emails..) to ensure privacy compliance.
Speech-to-Text: Accurately transcribe spoken language into text.
Code Analysis: Process programming code.
Image Analysis: Examine and interpret images using vision-based tasks.
Image Segmentation & Background Removal: Isolate subjects from backgrounds and segment image regions for advanced visual processing.
Document Layout Analysis: Detect and analyze document structures including paragraphs, lines, and layout elements for precise content parsing and extraction.
Optical Character Recognition (OCR): Extract text from images and scanned documents with multiple options: built-in OCR engine, pre-built integrations for external providers, or custom implementations through a unified interface.
Multi-Format Document Support: Multi-Format Document Support: Process diverse document families natively within your applications, including Office documents, PDFs, HTML, images, email formats, raw text, and more.
Model Quantization: Optimize models for efficiency.
Training Dataset Generation: Create custom training datasets for fine-tuning across classification, extraction, sentiment analysis, and other NLP tasks.
Model Fine-Tuning: Customize pre-trained models.
LoRA Integration: Merge Low-Rank Adaptation (LoRA) transformations into base models for efficient fine-tuning.
Plus More: Explore additional features to enhance your applications...
Unmatched Performance on any Hardware, Anywhere
LM-Kit aims to provide seamless Gen-AI capabilities with minimal configuration and top-tier performance across diverse hardware setups.
Whether deployed locally or in the cloud, LM-Kit is engineered to deliver optimal performance.
- Zero dependencies
- Native support for Apple ARM with Metal acceleration and Intel
- Supports AVX & AVX2 for x86 architectures
- Specialized acceleration using CUDA and AMD GPUs
- Hybrid CPU+GPU inference to boost performance for models exceeding total VRAM capacity
Trusted by Developers Like You
We partner with forward-thinking companies who share our commitment to innovation in AI. From technology providers to strategic collaborators, our partners play a key role in expanding what’s possible with LM-Kit. Together, we’re shaping the future of AI integration across industries.
