A solo operator just laid out how he sells on-premises RAG systems to law firms and clinics at €2,000 to €5,000, where every agency quote starts at $8,000 and climbs past $40,000. The pitch isn't AI. It's that no document ever leaves the building. EU rules kicked in on 2 August 2026, GDPR has been in force since 2018, and every partner who signs the invoice cares about one thing: a decade of contracts, invoices, and client records that cannot go to somebody else's cloud. The whole build runs on three pieces. An Nvidia GPU in the client's office runs the model via Ollama. A Python script converts the archive to Markdown. Obsidian becomes the window where staff type questions and get answers with links to the source documents. Claude writes the ingestion script, proposes the department taxonomy, drafts the runbook and the proposal. Then it comes out of the system entirely. Leave it in and every staff query flies to the internet, which kills the promise you sold. The step that decides whether he gets paid isn't the install. It's collecting 20 real questions from the actual users before the build, then running all 20 in front of them at handover. The number that come back correct with working source links goes in the contract as the acceptance criterion. That defines what "working" means before anyone can argue about it. Recurring software cost is zero. Ollama, Qwen models under Apache 2.0, bge-m3 under MIT, Obsidian free for commercial use since February 2025. The client pays for hardware once and electricity thereafter. Support and re-indexing run €200 to €500 a month. Build time on the first client is two to three weeks part-time, most of it ingestion and testing rather than setup. The second takes half that because the script, the vault layout, the runbook template, and the 20-question test all carry over. The value is not the technology. Any competent developer can wire RAG up. The value is assembling it on the client's own machine. Full breakdown in the article below.