Use case — Functional area

AI for document processes

Capture contracts, receipts and files automatically, classify them, file them in the right system. Three setup tiers from hosted with DMS connection to full-self-hosted with a local model — with an honest call on professional secrecy, GoBD and the confidence threshold above which a human steps in.

Law firms, tax advisors, administrations and mid-sized businesses spend a big share of their time on documents: reviewing contracts, allocating receipts, watching deadlines, filing records. That's core work highly qualified people spend on copy-paste and folder structures — not because they couldn't do better, but because the tools often stop at the PDF attachment.

can read documents, extract structured fields and flag unusual clauses — as a suggestion that gets reviewed and approved by a case worker. In regulated industries, this approval step isn't a comfort question but professional law.

Prerequisite in all tiers: a clear data model per document type and a calibrated confidence threshold above which a human steps in. Anyone not defining that doesn't automate case work — they automate errors, quietly and over months.

Three setup tiers

Which tier fits depends on three factors: sensitivity of the documents, volume and specialist-system landscape.

Tier 1

Hosted OCR with DMS integration

Tool mix

Hosted OCR and receipt classification (Klippa, Rossum, Konfuzio, Hypatos or the DMS's own OCR interface)
Existing DMS or case system (DATEV DMS, RA-MICRO, advoware, ELO, d.velop, M-Files) as target system
Workflow tool (Make, Zapier, n8n.cloud) for intake (mail, scan, upload) and handover into the DMS
Frontier LLM API for free extraction (contract clauses, deadlines) on top of structured OCR
Approval process: all automatic suggestions first land in an intake folder for sight-check

Fit

SMBs with moderate receipt and case volume without stricter professional-secrecy requirements. Tax advisors with standard mandates, administrations outside sensitive areas, trades businesses with contract management.

Effort & cost

Setup 5–10 days. Running cost approx. €100–500/month ( service by volume, , hosting).

Trade-off

Receipts and document content pass through SaaS services — usually with a DPA, often with EU hosting, but not all providers keep all data exclusively in the EU. Acceptable for standard receipts, the wrong tier for legal mandates or patient files.

Tier 2

Self-hosted pipeline with frontier LLM

Tool mix

n8n or a comparable workflow engine on your own server for intake, classification and handover
OCR still as a service or as an open-source variant (Tesseract, PaddleOCR) depending on receipt quality
Frontier LLM (Claude, GPT, Gemini) for free clause analysis, summaries and deadline extraction — with DPA, API calls leave the EU
Your own Postgres database for audit trail, receipt status, intermediate state and traceable history
Connection to DATEV, RA-MICRO, advoware or a comparable specialist system via certified interface, REST/SOAP or file export
Confidence thresholds: on uncertain hits the receipt is automatically lifted to manual sight-check — no silent auto-booking

Fit

Tax advisors, property managers and mid-sized businesses with several parallel workflows, claim to data sovereignty over intake and logs, and one person with responsibility.

Effort & cost

Setup 12–25 days. Running cost approx. €120–400/month (server, service if needed, ).

Trade-off

doesn't free you from upkeep: platform APIs, accuracy, clause templates go stale. Anyone not calibrating confidence thresholds regularly ends up with a pipeline that confidently hands over the wrong thing.

Tier 3

Full-self-hosted with local OCR and model

Tool mix

Tier 2 in full scope, all AI and OCR components local
Local language model (Llama 3, Qwen 2.5, Mistral) on a GPU server for clause analysis and classification — no document content leaves the house
Open-source OCR (PaddleOCR, EasyOCR, Tesseract) local, possibly with finely trained models for industry- or mandate-specific forms
Knowledge graph or structured index to capture mandate, file, contract and case relations — important in firm or multi-mandate structures
Full audit trail: every OCR hit, every AI statement, every approval is traceably documented — for GoBD, professional secrecy and internal compliance

Fit

Lawyers, tax advisors with sensitive mandates, healthcare providers, public sector — areas where professional secrecy or social-data protection practically excludes cloud services.

Effort & cost

Setup 25–45 days, plus hardware or server from €200/month. Local models in 2026 are very good at structured clause capture, noticeably behind frontier at free analysis.

Trade-off

Highest data control, highest effort. With local models, the escalation threshold to manual review should be set lower — a pipeline without a clear upkeep owner is particularly error-prone at this tier.

What your team should understand

Document automation only carries if professional responsibility stays in-house. Six competency areas that have to be anchored in every setup:

Document types and data model

Which document types are processed (invoice, contract, notice, correspondence, file) and which fields per type should be extracted. Without clean definition, turns into structured noise.

OCR fundamentals

Where is reliable (printed text, clear receipts) and where not (handwriting, poor scans, multi-column layouts). When custom models make sense and when a high-quality cloud service is the more honest choice.

Confidence and thresholds

How to read confidence — and why every receipt with low confidence belongs in manual sight-check. How thresholds get calibrated over time.

Contract and clause analysis

Which clauses are standard, which unusual, which should be there and aren't. What a model reliably handles here (first review, anomalies) and what it doesn't (legal assessment).

GoBD, professional secrecy, GDPR

What is required in terms of immutability, retention and traceability — and where automated workflows comply or jeopardise that. Which data categories practically rule out cloud processing.

Integration into DMS and specialist system

How receipts, files and cases land cleanly in the target system — with versioning, audit trail and link to the mandate or case. Which interfaces really carry and which only exist on paper.

What gets automated

Eight typical steps the pipeline takes over in running operations — at different depths depending on tier:

Intake pipeline

Documents from mail, scanner, upload portal or DMS intake are captured, deduplicated and routed into the right — one central intake address instead of five inboxes.

OCR and structured extraction

Per receipt type, fields are extracted (amount, date, VAT ID, mandate number, case reference, deadlines) and checked against master data.

Classification

Invoice, contract, reminder, notice, correspondence — automatic allocation with confidence figure and fallback into a sight-check folder.

Clause and deadline detection

first review of contracts: notice periods, liability and competition clauses, unusual agreements — flagged, not decided.

Allocation to mandate or case

Receipts are allocated to the right mandate and case by VAT ID, case reference or master data — duplicates and conflicts are flagged instead of overwritten.

Handover into the specialist system

Suggestion with all extractions to the DATEV, RA-MICRO or advoware counterpart, with reference to the original document. Approval stays with the case worker.

Deadline reminder

Detected deadlines flow into calendar or follow-up — with contract or case context, not as an anonymous entry.

Audit trail and weekly report

Which documents processed, which lifted to sight-check, where the pipeline was uncertain — narrative analysis instead of a status number without context.

What stays MANUAL on purpose

In regulated areas, auto-booking isn't efficiency, it's risk. These six points belong in human hands:

Legal and professional assessment

reviews, humans assess. What an unusual clause means, how to read a notice, which deadline triggers which legal consequence — belongs in professional hands, not in a .

Client secrecy and professional law

Which documents may flow through which pipeline at all — professional law, mandate agreements and data protection set limits the doesn't draw, the ownership does.

Approval before booking or sending

Booking suggestions, outgoing letters, notice responses — prepared automatically, approved manually. Silent auto-bookings in regulated areas aren't efficiency, they're risk.

Unclear and contradictory receipts

When or are unsure, the receipt belongs in human sight-check. The confidence threshold is a business decision, not a technical parameter.

Master-data and mandate upkeep

Wrong master data leads to wrong allocation on every subsequent receipt. A clear master-data owner is mandatory, not a detail.

Spot checks and quality assurance

Weekly check 10–20 cases against the original: are , classification, allocation correct? Without this discipline every pipeline silently loses accuracy over months.

How the build runs

From the document inventory to full self-operation usually 10–18 weeks, depending on tier, number of document types and specialist-system integration:

Document inventory

Which document types, what volume, current bottlenecks, what requirements. Captured in conversation, not from gut feel.

Data model per document type

Which fields get extracted, which are mandatory, which plausibilities apply. This definition caps the pipeline's quality long-term.

Choose the setup tier

Hosted, frontier or full-self-hosted — depending on sensitivity, volume, specialist-system landscape and data-protection ambition. Reasoned recommendation, you decide.

Build the pipeline

Intake, , classification, clause/deadline detection, allocation, handover into the specialist system — with clearly defined confidence thresholds and escalation into a sight-check folder.

Pilot with defined receipt type

Start with one or two clearly scoped document types (e.g. incoming invoices, standard contracts) — make success measurable before rolling out wider.

Training & hands-on handover

A 4–6-hour workshop with the responsible people: calibrate confidence thresholds, work through the sight-check folder, read the audit trail, interpret the weekly report.

Guided pilot month

Four weeks with weekly sparring: review real documents, adjust thresholds, extend clause templates, handle problems.

Self-operation with spot-check discipline

Clear responsibilities for master data and quality assurance. Optional: quarterly refresher on legal or tool changes.

Effort and investment depend on the chosen tier and the number of first document types — a concrete estimate comes after the document inventory and as part of the pricing overview.

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