An AI environment operating directly on your internal documents, processes, and corporate context – remaining strictly inside your private infrastructure. I evaluate the technical options, design the architecture and implement. Vendor-independent, with partners from my network for larger projects.
Assess Corporate LLM fit in a free AI Intro CallI implement. I take up your requirements, independently evaluate the technical options (open source vs. proprietary, on-premise vs. private cloud, RAG vs. fine-tuning) and build the system that fits you.
For larger projects I work with experienced partners from my network. I remain your technical point of contact and make sure the result fits your operations.
Post-deployment, I support your leadership through the initial months of live operation. This is where most Corporate LLM initiatives fail: not in technical deployment, but in operational adoption.
We clarify whether your compliance requirements justify a Corporate LLM or if a simpler alternative is better suited.
We test real operational tasks within one department to validate functional requirements before committing capital.
Requirements, architecture, technical evaluation, implementation and rollout.
A Corporate LLM is a dedicated AI language model environment deployed inside your private infrastructure. Sensitive data never leaves your company boundary, allowing the model to work directly with your internal documentation, processes, and corporate context.
Whenever one of three criteria applies: your data cannot leave your internal network (personnel records, legal contracts, customer data, source code), the model must query internal knowledge, or AI adoption is blocked by privacy concerns. If none apply, public tools are usually more cost-effective – and I will candidly tell you so.
Yes, that is the foundational principle. A Corporate LLM processes data within your private infrastructure, whether on-premise or in a private cloud. Which deployment model fits your security requirements is determined independently during initial architecture planning.
Not necessarily. Depending on security requirements, a private cloud setup may suffice; in other cases, on-premise hosting is necessary. I independently evaluate vendor options (open source vs. proprietary, on-premise vs. private cloud) and recommend what fits your compliance needs and budget.
Three steps: a free 30-minute AI Intro Call, followed by a Use Case Sprint with one department to determine operational requirements, and finally architecture and implementation. I remain your technical point of contact and support you through the first months of productive use.
A Corporate LLM is a significant enterprise investment. Before allocating budget, we clarify in a free AI Intro Call whether it truly fits your requirements – or if a simpler alternative achieves the same result.