LM-Kit
LM-Kit builds a private AI stack for intelligent information management: LM-Kit One serves models, agents, RAG, search and document intelligence on customer-controlled infrastructure, while LM-Kit.NET embeds the runtime inside .NET applications. Its stated mission is to make private AI practical and keep AI running where the data lives.
At a Glance
- Organizations with sensitive or regulated information
- Software vendors, ISVs, OEMs and system integrators
- Public institutions, education and healthcare
- Enterprise content and intelligent information management teams
- +2 more
AI Tools by LM-Kit
(1)
LM-Kit One
Self Hosted AI API Server
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Latest News
Private AI or Local AI? What differs, and why both terms exist
LM-Kit One Is Here: Private AI, Under Your Control
LM-Kit One Arrives September 15
Agent Skills Explained: Turn Any Agent Into an On-Demand Specialist with SKILL.md
Products & Services
Embedded private AI runtime for .NET: local inference, agents, RAG, search, document intelligence, vision, speech, embeddings and model optimization in one in-process SDK, with no required cloud calls, Python runtime, Docker or daemon.
Private AI application server for Windows, Linux and macOS. It serves models, agents, RAG, search, document processing and extraction behind native REST and OpenAI-, Anthropic-, Ollama- and MCP-compatible interfaces, with governance, identity, policies, audit and horizontal scaling.
Secure desktop application in the LM-Kit GitHub organization for orchestrating AI agents offline and building personalized chatbots with LM-Kit.NET.
Professional audio transcription application built with .NET MAUI and powered by LM-Kit.NET.
Market Position
LM-Kit positions itself as a unified private AI stack rather than a model-serving endpoint or a collection of separately maintained components. LM-Kit.NET targets .NET developers who otherwise combine inference, document processing, vector search, RAG and agent frameworks; LM-Kit One extends the same engine to a governed server with familiar OpenAI, Anthropic, Ollama and MCP interfaces. The company explicitly compares its products with Ollama, vLLM, LM Studio, Foundry Local, ONNX Runtime GenAI, LLamaSharp, LangChain, LlamaIndex, Semantic Kernel and Microsoft agent frameworks.
Leadership
Founders
Loïc Carrère
Entrepreneur and programmer focused on digital imaging, software architecture, complex algorithmic systems and enterprise software; founder of LM-Kit and President of LM-KIT.
Executive Team
Loïc Carrère
President of LM-KIT; Founder
Entrepreneur and programmer with a background in digital imaging, software architecture, complex algorithms and enterprise software; identified by LM-Kit as the founder and by the 2024 launch release as CEO.
Founding Story
LM-Kit started inside the Calico IIM Group as a response to the belief that enterprise AI should run beside the data it works on, under the laws and controls of the organization that owns it. The team spent roughly three years rebuilding inference, document processing, retrieval, search, agents and operational controls as one private, local-first stack; LM-Kit.NET launched publicly in 2024 and the stack later became LM-Kit One.
Business Model
Revenue Model
Free download and licensing model. Evaluation and development are free without a time limit; production use is free below the published thresholds and for personal use, education, nonprofits and open-source projects. Above the thresholds, LM-Kit sells an annual Professional License scoped per application for LM-Kit.NET or per deployment for LM-Kit One, priced on scope rather than tokens, seats or usage.
Pricing Tiers
No key and no expiry. Commercial use and redistribution for companies under $1M annual gross revenue, 10 or fewer employees and no more than $3M raised from outside investors; evaluation/development is free at any company size. Also always free for personal, education, nonprofits and open source.
Required above the free thresholds; production and redistribution rights, long-term support/security patches and response-time commitments are scoped in the order. Priced by application scope for LM-Kit.NET or deployment scope for LM-Kit One, not by tokens or seats.
Target Markets
- Organizations with sensitive or regulated information
- Software vendors, ISVs, OEMs and system integrators
- Public institutions, education and healthcare
- Enterprise content and intelligent information management teams
- Developers building desktop, edge, offline and air-gapped .NET software
- Small businesses and startups seeking local AI without per-token cloud costs
- Private company knowledge and cited internal-document assistants
- Invoice, contract, form and ID structured-data extraction
- Agentic document workflows and multi-agent document review
- PII detection, review and permanent redaction
- Enterprise search, multi-tenant search and RAG
- Customer-support automation and meeting/call transcription