What does on-premise or fully offline AI document processing require?
Three things: hardware with enough GPU memory for the chosen models, a software chain of extraction, models and verification that runs without internet access, and an operating process for updates, monitoring and model changes. How large that turns out depends mainly on document volume and the required depth of verification.
Hardware
Large models need several data-centre GPUs with a lot of memory; smaller models need less. Sizing depends on document volume, required turnaround and how many models run in parallel – for example for the independent second verification pass.
Software
- Layout analysis and OCR for the baseline extraction.
- Local inference servers for the language models.
- The verification chain: provenance, control totals, literal grounding, double pass.
- Verification reports and logging for audit.
Running fully offline
Without internet, models and updates must be brought in under control. Telemetry and automatic updates are switched off, and model licences must permit offline use. Monitoring and troubleshooting happen entirely inside your own network.
Governance
Who has access, what is logged, how are model changes documented? These questions belong in from day one – including with the EU AI Act in mind.
How to start
With an analysis of real sample documents, sizing of hardware and models, and a pilot. After that it is clear whether running it yourself pays off or a sovereign provider fits better.