Comparison
feld.ai vs. Konfuzio — document AI on owned hardware
Konfuzio (Helm & Nagel GmbH) and feld.ai solve the same problem: reading, classifying, extracting and verifying documents automatically. Both come from the German-speaking market, both advertise European processing. The difference sits one layer down — in who owns the hardware your documents are processed on.
Where the difference actually is
Owned hardware, not European cloud. "Hosted in Europe" describes a location, not an ownership structure. If processing runs on a hyperscaler with a US parent, the location is European but the operator is not. feld.ai runs its own GPU servers in Feldkirch — the machines are ours, they sit with us, and they fall under European law only. For many workloads that distinction does not matter. For personnel files, customs documents and contracts it becomes the conversation with your data protection officer.
Independent and founder-led. feld.ai decides its roadmap independently — no parent group, no suite the product has to accommodate. Customers talk directly to the team that builds the models.
Where Konfuzio is ahead. Konfuzio states ISO 27001; ours is in preparation. If your procurement lists a valid certificate as a minimum requirement, that is a legitimate argument against us — and you are better off learning it here than three weeks into a vendor questionnaire.
Detailed comparison
| Criterion | feld.ai | Konfuzio |
|---|---|---|
| Vendor | feld.ai GmbH | Helm & Nagel GmbH |
| Headquarters | Feldkirch, Austria (EU) | Germany (EU) |
| Processing | Own GPU servers in Austria | Hosting in Europe |
| Own AI models | Yes — fully in-house models | Yes |
| Template-free extraction | Yes | Yes |
| Visual grounding | Yes — every value traced to its source location | Not publicly stated |
| On-premises | Yes | On request |
| ISO 27001 | In preparation | Stated |
| Pricing model | €400 per active user per month; further costs depend on scope | On request |
| Point of contact | Direct access to the engineering team | Sales channel |
How to compare the two properly
Feature tables rarely decide these selections correctly, because on paper both vendors do almost the same thing. What actually separates them only shows up on your documents: poor scans, multi-page annexes, line-item tables, and suppliers whose layout changes twice a year.
So take 200 real documents from live operations — not ten flattering ones — and run both systems against them. Measure field-level accuracy, but above all: do the systems report uncertainty where they are wrong? A model that states incorrect values confidently costs more than one that is slightly less accurate and reliably flags it.
For the legal grounding behind sovereignty claims, see EU-sovereign document AI. If you are instead considering building extraction yourself on a frontier model: feld.ai vs. building it yourself.
Frequently asked questions
What is the difference between feld.ai and Konfuzio?
Both are intelligent document processing vendors from the German-speaking market. Konfuzio is operated by Helm & Nagel GmbH in Germany and advertises European hosting. feld.ai runs its own GPU servers in Feldkirch, Austria — processing happens on hardware the vendor owns, not at a cloud provider. If you audit data sovereignty down to the hardware layer, that is the material difference.
Is Konfuzio ISO 27001 certified?
Konfuzio states ISO 27001 on its website. At feld.ai, ISO 27001 certification is currently in preparation. If an existing certificate is a hard requirement in your procurement process, that is a point in Konfuzio's favour — we would rather say so here than have it surface three weeks into a vendor questionnaire.
Where is data processed in each case?
Konfuzio states European hosting. feld.ai processes all data on its own GPU servers in Austria, with no US subprocessor in the chain. The difference is less about the country than about who owns the infrastructure: hardware you own is not exposed to CLOUD Act access through a US parent company.
Can feld.ai replace Konfuzio?
For the core capabilities, yes: classification, template-free extraction, validation against master data, human-in-the-loop review and visual grounding. Migration runs through a REST API. Whether switching is worthwhile depends on your document mix, which is why we recommend running both systems in parallel on real documents rather than comparing feature lists.