I will build a local rag knowledge base for company documents


About this gig
Your company knowledge is often scattered across PDFs, manuals and folders. I build local RAG prototypes that retrieve relevant passages and return answers with traceable source references. The model and vector store are selected for your hardware and requirements. Typical building blocks include Ollama and a local vector database such as Qdrant. The package and data scope are confirmed before work starts; no cloud service is included unless we agree to it explicitly.
You receive a prototype sized to the selected package, sample-question testing, written setup notes and, for Premium, a handover walkthrough. We can also arrange a practical team workshop on using and maintaining the system.
Please message me first with document types, approximate volume, available hardware and intended users. Use anonymized sample files for initial scoping. Production hardening, hosting, security certification, migration from confidential systems and guaranteed answer accuracy are not included unless separately agreed.
Get to know Mike
Reliable data, no drama
- FromGermany
- Member sinceMay 2026
Languages
English, German
My Portfolio
FAQ
Does the RAG system run fully offline?
The intended setup is local with Ollama and a local vector store. Whether it is fully offline depends on your hardware, models and integrations. We confirm the data flow before work starts; cloud connections are not enabled by default.
What do you need before estimating the scope?
For initial scoping, share document types, approximate volume, intended users and available hardware. Anonymized sample files are enough to start. Any access to confidential production data or systems must be discussed and agreed separately.
Are accurate answers or GDPR compliance guaranteed?
No. Results depend on the documents, model, retrieval settings and question. I test agreed sample questions and include source references, but I cannot guarantee every answer or provide legal certification.

