Large Language Model (LLM)
A large language model is an AI system trained on vast amounts of text, capable of understanding and generating human-like text.
What is a Large Language Model (LLM)?
A Large Language Model (LLM) is a type of AI model trained on billions of text fragments from books, websites, and other sources. Through this training, the model has developed a deep understanding of language structure, context, and meaning. LLMs can generate text, answer questions, create summaries, translate, and follow complex instructions. Well-known examples include GPT, Claude, and Llama.
How does an LLM work?
An LLM works by recognizing patterns in the vast amount of text it was trained on. When you ask a question, the model analyzes the context and generates an answer step by step based on statistical probability. Wabber runs LLMs on its own private cluster with 128GB of VRAM, distributed across professional GPUs. Combined with our RAG pipeline, models are enriched with your company-specific knowledge, ensuring answers are relevant and reliable for your organization.
Example
A logistics company implements an internal knowledge system through Wabber based on an LLM. Employees can ask questions in natural language such as 'What is the return policy for client X?' or 'How many pallets were processed this week?'. The LLM, enriched with company documentation via the RAG pipeline, provides an immediate reliable answer. This saves hours of search time per week and reduces errors from incorrect interpretation of procedures.
Why are LLMs important for businesses?
Deploying LLMs offers businesses enormous possibilities: from intelligent chatbots that answer customer questions 24/7 to internal knowledge systems that help employees find information. Importantly, your data stays private: at Wabber, all processing is performed on our own hardware in the Netherlands, not with external cloud providers. Wabber guides you in selecting the right model and ensuring privacy in line with our upcoming ISO 27001 certification.
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Frequently asked questions
What is the difference between an LLM and a chatbot?
An LLM is the AI model that understands and generates language. A chatbot is the application that uses this model to conduct conversations with users. The LLM is the engine; the chatbot is the vehicle. Wabber builds chatbots based on LLMs running on our own private cluster in the Netherlands.
Why does Wabber run LLMs on its own hardware?
By running LLMs on our own hardware in the Netherlands, we guarantee your data is not sent to external cloud providers. All processing takes place on our private cluster with 128GB VRAM. This is essential for organizations working with sensitive business or customer data and complying with GDPR legislation.
What is RAG in combination with an LLM?
RAG (Retrieval-Augmented Generation) is a technique where an LLM is enriched with your company-specific documents and data. When a user asks a question, the system first retrieves relevant information from your knowledge base and adds it to the LLM's context. This way, the model provides answers based on your own data rather than only on general training data.
Which LLM models does Wabber support?
Wabber supports multiple open-source and commercial LLM models, including Llama, Mistral, and other state-of-the-art models. We advise per use case which model best fits based on task, language, speed, and privacy requirements. All models run on our own private cluster in the Netherlands.
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