Accounting support in a tax advisory firm
A tax advisory firm pre-processes receipts and booking proposals locally: documents are extracted, categorized and matched to the books — client data never leaves the building.
Built with: Dify, Docling
// CONTROL ROOM — LOCATION: YOUR BUILDING
Local. With you Open source Independent Secure
These four use cases are ones we already deliver for customers today on the rzfz.ai Stack — the integrated open-source stack for local AI infrastructure. Describe your own business in the use-case finder for scenarios tailored to you.
A tax advisory firm pre-processes receipts and booking proposals locally: documents are extracted, categorized and matched to the books — client data never leaves the building.
Built with: Dify, Docling
An IT service provider serving many SMBs receives hundreds of log and support emails daily. A local workflow classifies them, separates noise from real incidents and prioritizes what a human needs to see.
Built with: Dify
A local coding agent works around the clock on the in-house repository: writing unit tests, steadily raising coverage and opening merge requests — with no code ever leaving the infrastructure.
Built with: Codex, OpenCode, gsd-pi, Gitea
Inbound customer documents are extracted locally and sensitive data is redacted automatically before further processing — built together with PSA, awarded the Constantinus Award 2026.
Built with: Docling, Presidio, Dify
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In principle, yes. The main difference is model size. Cloud AIs like ChatGPT run huge models with knowledge you'll probably never need for your use case. For local AI, we recommend specialized models instead (one for image recognition, one for code, and so on). The goal isn't to rebuild ChatGPT locally — it's to leave out the parts you'll never use.
True — and that's actually a benefit for the environment too. The Box is built to be energy-efficient for local, targeted requests and process support. Cloud providers scale in parallel for millions of users and consume power accordingly. Local AI achieves the same or better results with less compute, because it runs smaller, specialized models.
Yes. We've built many AI agents and automation workflows for our own use, and we offer these as a template subscription. Whenever we optimize a workflow or build a new one, our subscribers get the updated templates automatically and can build on them or create their own versions.
Three options: (1) We handle everything remotely under a maintenance contract. (2) You maintain the Box yourselves. (3) You want to maintain it yourselves but need the know-how — for that, we offer training that covers everything you need to know to run it in a way that is compliant with GDPR and the EU AI Act.
We use hardware architectures with unified memory, where the GPU can also use the main system memory. Dedicated GPU cards often draw 800–1,000 W; our hardware draws 30–300 W. We handle procurement, pre-installation, and configuration for you. For a small installation fee, we'll even set it up on-site if you're in the greater Vienna area.
The rzfz.ai Stack: curated open-source modules for local AI infrastructure — runs on the Box, your own servers, or the cloud.
Learn more →Pre-configured hardware and software bundles with the rzfz.ai Stack — from starter set to enterprise.
Learn more →AI engineering, integrations and custom extensions — consulting and digitalization by our partner SEQIS.ai.
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