Solution pattern · reference architecture
Document pipeline with mandatory approval.
This pattern reads selected order or invoice documents, compares fields with master and transaction data, and presents differences for review. A posting or business decision is never made solely from the model output.
Starting point
Orders and invoices arrive in changing formats and need review under time pressure.
PDFs, scans, and emails contain fields that employees transfer into ERP or business systems and compare with purchase orders, prices, or supplier records. Plain text recognition identifies neither business differences nor approval limits.
Business value
Suggestions, rules, and approval become one traceable workflow.
Standard fields can be prepared in a structured form, differences can be prioritised by business relevance, and every correction can be documented. Accountable employees retain approval.
What becomes measurable
- Recognition quality by document type, field, and layout
- Frequency and cause of business exceptions or manual corrections
- Status, waiting time, and queries in the approval workflow
Reference architecture
Components and their purpose
The original is retained, extraction and business rules are separated, and only approved data reaches the target system.
- 01
Secure intake and original
Email, upload, or scanner sends permitted files to Azure Blob Storage. Format, malware checks, source, and arrival time are recorded.
- 02
Extract fields
Azure AI Document Intelligence reads layout, tables, and relevant fields with confidence values from a suitable prebuilt or custom model.
- 03
Apply business rules
Azure Functions compares supplier, order, amounts, tax details, or items with approved master and transaction data.
- 04
Keep people in control
Azure Logic Apps and a Power App or existing business interface present the original, suggestion, difference, and change history for approval.
- 05
Transfer approved data
Azure Service Bus or a controlled API sends only confirmed data to ERP or the business system. Failures enter a visible queue.
- 06
Monitor quality and operations
Azure Monitor records technical errors, correction patterns, and model changes. Training data and model versions remain traceable.
Technology
Concrete services for implementation
The selection is adapted to existing contracts, regions, security requirements, and the actual scope.
- Azure Blob Storage
- Azure AI Document Intelligence
- Azure Functions
- Azure Service Bus
- Azure Logic Apps
- Power Apps
- Azure Key Vault
- Azure Monitor
First project scope
A pilot needs clear boundaries
The first deployment tests data, integration, and the working process in a limited area. It is not a premature enterprise rollout.
Deliberately included
One frequent document type from a named intake channel, selected fields and business rules, test access to the target system, and human approval before every transfer.
Deliberately excluded
No unattended posting, full archive migration, processing of every language and handwriting style, or decision about payment, credit, or contract based solely on the model.
Prerequisites and constraints
Technology does not replace data accountability
Data access, responsibilities, licences, and operations must be clear before implementation. Open points are treated as project risks.
- 01Legible and lawfully usable sample documents must represent real layouts and exception cases.
- 02Supplier, item, purchase-order, and tax data need maintained keys and unambiguous business rules.
- 03The ERP interface, test environment, approval roles, and failure handling must exist before production transfer.
- 04The business function, ERP owners, data protection, information security, and where relevant the works council must bound the process together.
Germany and the EU
Compliance follows the specific purpose
Documents can contain names, contact details, bank information, and other personal data. GDPR purpose limitation, data minimisation, retention, deletion, and role-based access are therefore part of the design. Suitable EU regions and the AI service's specific processing paths must be checked. The intended purpose must be classified under the EU AI Act, with transparency and human oversight documented. If processing or performance data about employees is created, co-determination under the Works Constitution Act must be reviewed.
Free initial assessment
Which document type requires the most business review today?
The discovery call can bound intake, fields, business rules, approval, and deliberate exclusions.
The initial consultation and joint use-case discovery are free and non-binding.
Related use cases
Automated order and document validation
Orders arrive as PDFs, spreadsheets, emails, or free text. Differences in items, quantities, prices, or addresses are often found late.
Compliance and audit evidence retrieval
Evidence sits in tickets, policies, training lists, approvals, and emails. Currency, completeness, and provenance are difficult to see.
Intelligent contract and case-file search
Contracts, amendments, and filings are distributed. Relevant clauses sit in full text while search and deadline lists depend on file names.