Local AI for industry & engineering – Ollama, RAG and company data
Make technical documents and internal project knowledge easier to use. We develop local AI applications for industry and engineering and integrate them into existing software and workflows.
Ollama: language models within your company
Ollama can run language models on a suitable workstation or company server. We match the model, hardware and response times to the task. Fully local operation also depends on supplementary services and the chosen configuration.
RAG: answers grounded in your documents
Retrieval-Augmented Generation finds relevant passages in your documents and provides them to the language model as context. An assistant can then present information from manuals or project documentation with source references. Quality is assessed using concrete questions and reference answers.
Qdrant and structured knowledge collections
Qdrant can serve as a vector database to retrieve semantically relevant text passages. Document versions, project assignments and permissions must be handled by the overall system. Updating the knowledge collection is part of the operating plan.
PDFs, manuals and technical documentation
We prepare documents for search, analysis and classification. Digital PDFs and scans require different processing; scans need suitable text recognition. Sample documents are used to assess extraction, retrieval and answer quality.
Engineering assistants and C#/.NET integration
An assistant can make project knowledge searchable, summarise technical content and prepare drafts. C#/.NET can integrate it into an existing application. Technical review and clear source references remain part of the workflow.
From pilot to operation
We start with a limited collection of documents and typical user questions, then evaluate model quality, hardware needs, permissions and maintenance effort. Expansion to further projects or departments follows that assessment.
Related project experience
Related software products
Frequently asked questions
Can AI run entirely within our company?
Yes, with a suitably designed solution. Models, embeddings, document processing and databases must run locally, with external services excluded. We assess hardware and operational requirements beforehand.
Can local AI search technical documents?
Yes. Documents are processed and relevant passages retrieved. A RAG assistant can produce answers with source references, while respecting the access controls implemented by the system. Document quality must also be assessed.
Does RAG require training a new language model?
A typical RAG solution does not require custom model training. Relevant document excerpts are supplied with the request. Model selection and retrieval quality still require targeted testing.
Let’s discuss your project
Tell us about your task, existing systems and intended use.