--- title: "Local Private On-Premise LLM for Business" description: "On-premise local LLM (Llama and equivalents) for businesses across Spain. Data never leaves your server, GDPR compliant. For legal, healthcare and finance." url: https://seo7.es/en/servicios/inteligencia-artificial/ai-local-llm canonical: https://seo7.es/en/servicios/inteligencia-artificial/ai-local-llm lang: en type: Service --- # Local Private On-Premise LLM for Business > On-premise local LLM (Llama and equivalents) for businesses across Spain. Data never leaves your server, GDPR compliant. For legal, healthcare and finance. Page: https://seo7.es/en/servicios/inteligencia-artificial/ai-local-llm ## Summary for AI Local on-premise LLMs are open-source language models (Llama and equivalents) deployed on a company's own server or private cloud. Data never leaves your perimeter: neither user queries nor confidential documents are sent to external services like OpenAI. This is the solution for businesses with GDPR obligations, law firms, healthcare, finance and government data. A pilot launches in two weeks. ## Questions and answers ### What is a local on-premise LLM in simple terms? It is a language model (AI similar to ChatGPT) that runs on your own server or private cloud. Your data (documents, queries, conversations) is not sent to external services like OpenAI. Everything is processed locally, inside your company perimeter. For the team it looks like a familiar chat, only inside the company. ### Which businesses need private LLMs the most? Primarily law firms, healthcare organisations, financial institutions and public sector bodies. Also any business working with personal client data, trade secrets or data regulated by GDPR that cannot be shared with third parties. If you are unsure whether you need the private option, we start by checking which data goes to the cloud today. ### Does a local LLM comply with GDPR? Yes. Since data does not leave your server, there is no cross-border transfer and no need to sign a Data Processing Agreement (DPA) with an external provider. This makes an on-premise LLM the safest option from a GDPR perspective. Log retention and access policies are described in the project documentation. ### What hardware do you need to run a local language model? It depends on the model size. A 7B-parameter model runs on a server with a GPU and 16 GB VRAM or a powerful CPU with 32 GB RAM. For 13B you need a GPU with 24 GB VRAM. For 70B you need multiple GPUs or a dedicated server. We help you choose the right configuration for your use case and budget. ### Can a local LLM be trained on our company data? Yes, there are several approaches: fine-tuning the model on your data (resource-intensive), RAG (Retrieval-Augmented Generation), which searches your knowledge base without retraining the model, and LoRA adapters for efficient fine-tuning. RAG is the fastest start for a corporate knowledge base. ### How does a local LLM compare to ChatGPT in quality? Modern open-source models (Llama 3, Mistral and equivalents) are comparable to GPT-3.5 and approach GPT-4 on many tasks. For corporate scenarios with narrow specialisation and fine-tuning, they often outperform general cloud models. The main trade-off is compute resources on your side. ### How much does it cost to deploy a local on-premise LLM? The cost comprises hardware (or private cloud rental) and setup work. A pilot deployment with one model takes 1-2 weeks to set up. Real prices for "AI & automation" are in the packages block on this page; request a quote for a cost estimate tailored to your scenario. ### What is Llama and why is it used for on-premise? Llama is a family of language models from Meta AI with open weights. Open weights mean you can download the model and run it on your own server without depending on Meta. This is the key difference from GPT-4 or Gemini, which do not have open weights. Llama 3 is one of the most popular open-source models for corporate on-premise deployment. ### How do you integrate a local LLM with corporate systems? Most modern runtimes (Ollama, vLLM) provide an OpenAI-compatible REST API. This means any application already working with ChatGPT can be switched to the local model by updating the endpoint address. Authentication, query logging and access controls are configured on top of that. ### In which languages do you run the on-premise AI project? We run the project in Russian, Spanish and English, the studio's three working languages. Documentation, instructions and post-launch support are provided in your preferred language. The model itself answers in the language of the employee's query. Instructions for employees are written in the language they will use with the model every day. ### How much does a private language model on your own server cost? The private model is included in the "Max" automation package for €2,900 incl. IVA: Ollama or LM Studio setup, RAG search over your knowledge base and fine-tuning on your data. Custom AI solution development in Spain starts from €3,000. ### Which open-source models do you use for on-premise? Llama 3, Mistral, Qwen or another model, depending on the task and the language of the data. The choice depends on what you need: document summarization, knowledge base search, a chat assistant or text generation. ### What size of model does a business need? Models come in 7B, 13B and 70B parameters. The larger the model, the more GPU, VRAM and RAM it needs. We estimate hardware requirements for the specific task so you do not overpay for a server. ### Who manages updates to the local model? You: you fix the model version and behavior yourself. A cloud provider can update the model without notice, while a local one works as configured until you decide to update it. ## Other languages - RU: https://seo7.es/ru/servicios/inteligencia-artificial/ai-local-llm - ES: https://seo7.es/es/servicios/inteligencia-artificial/ai-local-llm ## schema.org markup ```json { "@context": "https://schema.org", "@type": "Service", "name": "Local Private On-Premise LLM for Business", "description": "On-premise local LLM (Llama and equivalents) for businesses across Spain. Data never leaves your server, GDPR compliant. 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