AI-Powered Document Processing
Your team is spending hours keying data from documents into your ERP. That’s not a staffing problem — it’s a systems problem.
Every month, your operations team processes hundreds — sometimes thousands — of invoices, purchase orders, bills of lading, claims forms, and certificates of analysis. Most of that work is still manual. Someone opens a document, reads it, types the data into a system, and hopes they didn’t transpose a number. Multiply that across every vendor, every format, every department — and the cost becomes hard to ignore.
Weidenhammer’s AI-Powered Document Processing solution reads documents in any format, extracts the data that matters, validates it with built-in confidence scoring, and routes it directly into your existing ERP or workflow system. Deployed to your own Microsoft tenant for full data ownership and security control.
If You’re Asking Yourself These Questions, This Solution Is for You
“We have a team of people manually keying data from documents into our ERP — how do we stop that?”
“Our document volume is growing but our headcount can’t keep up. What are our options?”
“We’ve looked at OCR tools before, but they can’t handle our variety of document types. Is there something better?”
“How do I get structured data out of unstructured documents without building a custom AI solution from scratch?”
What Will You Gain?
80–90% Reduction in Manual Document Processing
The solution handles extraction, validation, and routing automatically. Your team reviews only the exceptions — documents that fall below confidence thresholds — while the rest flow straight through. One client cut manual data entry by 88% within six months of deployment.
Full Data Ownership and Security
Unlike SaaS document processing platforms that route your data through third-party infrastructure, this solution deploys directly to your Azure tenant. Your data never leaves your environment. Azure Entra ID provides SSO and role-based access control out of the box.
Processing Time from Hours to Minutes
Documents are processed in under 60 seconds. What used to take a team of data entry specialists an entire shift now happens in near real-time, accelerating order-to-cash, procure-to-pay, and claims processing cycles.
3x+ Return on Investment Within 6 Months
Between labor savings, error reduction, and faster cycle times, organizations typically achieve 3x or greater ROI within six months. One client achieved 3.5x ROI in that same timeframe.
Any Document, Any ERP
The platform is ERP-agnostic and handles any document type — invoices, purchase orders, bills of lading, certificates of analysis, insurance claims, medical records, contracts, and more. If it contains data your business needs, this solution can extract and structure it.
How Does This Help Your Operations and IT Teams?
Operational Capacity Without Headcount
Your operations team stops spending their days re-keying information. The people currently entering data shift to exception handling, vendor management, process improvement — work that actually moves the business forward.
IT Gets a Turnkey Platform, Not a Build Project
This isn’t a “bring your own AI team” situation. Weidenhammer delivers a fully deployed, Azure-native platform via Infrastructure as Code. Your IT team gets a production-ready system with SSO, RBAC, monitoring, and API documentation — not a proof of concept that needs six more months of engineering.
Extensible for Future Use Cases
Start with invoice processing or purchase orders, then expand to claims forms, certificates of analysis, contracts, or any other document type. Custom schemas are added as straightforward extensions — no re-architecture required. The platform also opens the door to downstream AI use cases: data lakehouse integration, workflow automation, and AI agent development.
Proactive Risk Reduction
Dual confidence scoring and human-in-the-loop review catch errors before they enter your ERP. Automated audit trails and structured data output reduce compliance risk in regulated industries.
Addresses the Following Challenges
Manual Data Entry at Scale
Your team spends hours re-keying information from invoices, POs, packing slips, and other documents into your ERP. It’s slow, error-prone, and pulls skilled staff away from higher-value work. As volumes grow, the problem compounds — more people, more errors, more cost.
Document Variety and Complexity
Traditional OCR and template-based tools break when document formats change. You receive documents from dozens of vendors in different layouts — PDFs, scanned images, Word files, spreadsheets — and rigid tools can’t adapt. Every new vendor or format means another template to build and maintain.
Compliance and Accuracy Risk
Manual processing introduces transcription errors that cascade through downstream systems. In regulated industries — food manufacturing, healthcare, insurance — a single miskeyed lot number, policy number, or dosage can trigger compliance violations, costly recalls, or claim denials.
Disconnected Systems and Bottlenecks
Documents arrive via email, FTP, portals, and physical mail. Without automated ingestion and routing, they sit in queues waiting for human attention. Processing cycle times stretch from minutes to days, delaying order fulfillment, payment processing, and operational decisions.
How It Works
The solution uses a four-stage AI pipeline built on Microsoft’s Azure AI platform, including Azure OpenAI (GPT-4o) and Azure AI Content Understanding:
1. Extract
Documents can be ingested from email, file upload, or API. The AI engine reads the full document — text, tables, handwriting, images, and graphs — regardless of format (PDF, Word, scanned image, TIFF, PNG, JPEG).
2. Map
Extracted content is mapped against predefined or custom schemas. The system identifies which fields correspond to which data points — invoice number, line items, quantities, dates, totals — and structures the output as clean JSON ready for downstream consumption.
3. Evaluate
Every extraction is scored with dual confidence metrics: a field-level confidence score and an overall document confidence score. Documents meeting your configured thresholds pass through automatically. Those below threshold are flagged for human review in a built-in web interface.
4. Save and Route
Validated data is saved to your data store (Azure, AWS, or your preferred target) and routed to your ERP, workflow, or data platform via API integration. Split, merge, batch archive, and pagination capabilities handle high-volume and multi-page document scenarios.
Solution Capabilities
Multi-Modal Document Intelligence
Process PDFs, Word documents, Excel spreadsheets, scanned images (PNG, JPEG, TIFF), and mixed-media documents containing text, tables, charts, and handwriting. The AI adapts to new layouts without template configuration — unlike legacy OCR tools that require a new template for every document variant.
Schema-Based Extraction with Custom Schemas
Define exactly what data to extract using configurable schemas. Start with industry-standard schemas for common document types (invoices, POs, BOLs) and extend with custom schemas for specialized documents unique to your industry. Output is structured JSON, ready for integration.
Human-in-the-Loop Review
When confidence scores fall below your configured thresholds, documents are queued for human review in a purpose-built web interface. Reviewers validate and correct extractions, and the system learns from corrections over time. This ensures accuracy without sacrificing throughput.
Automated Email Ingestion
Documents arriving via email are automatically captured and fed into the processing pipeline. No manual download-and-upload steps. This is critical for organizations receiving hundreds or thousands of vendor documents via email daily. A variety of email ingestion tools and connectors can be configured to match your existing environment.
Enterprise Security and Access Control
Deployed to your own Azure tenant with Azure Entra ID for single sign-on and role-based access control. Data never leaves your environment. Infrastructure is provisioned via Infrastructure as Code (Bicep templates) for repeatable, auditable deployments.
Document Management: Split, Merge, and Archive
Handle multi-page documents that contain multiple logical records (e.g., a single PDF with 50 invoices). Split them into individual documents, merge related documents, and batch archive processed files — all within the platform.
API-First Architecture
Every capability is accessible via REST API endpoints, enabling integration with any downstream system — ERP, data lakehouse, workflow engine, or custom application. The platform runs on Azure Container Apps for scalable, serverless compute.
How Weidenhammer’s Solution Compares
- Choose Weidenhammer’s AI Document Processing if you want a pre-built, Microsoft-native solution deployed to your own tenant with full data ownership, multi-document-type support, and white-glove integration services.
- Choose a per-document SaaS platform (Kofax, ABBYY, Rossum) if you prefer a hosted model, process primarily one document type, and don’t require data residency control.
- Choose a DIY approach if you have a dedicated AI/ML engineering team and want to build extraction models from scratch — but expect 6–12+ months of development before production.
- Choose your ERP’s native document capture if you only need invoice processing for a single ERP and don’t require multi-format or multi-document-type support.
| Criteria | Comparison |
| Deployment Model | Weidenhammer deploys to your Azure tenant (IaC). SaaS competitors (Kofax, ABBYY, Rossum) host on their infrastructure. DIY requires you to build and manage your own. |
| Data Ownership | Your data stays in your infrastructure / cloud with Weidenhammer. SaaS platforms process data on third-party servers. ERP native tools stay within ERP but are limited in scope. |
| Document Type Support | Weidenhammer handles any document type across any industry (invoices, POs, BOLs, claims, COAs, contracts, medical records, and more). ERP native tools typically handle invoices only. SaaS platforms vary by vendor. |
| ERP Compatibility | Weidenhammer is ERP-agnostic — works with Dynamics 365, SAP, NetSuite, Oracle, or any system with an API. ERP native tools are locked to their platform. SaaS tools require custom integration. |
| Pricing Model | Weidenhammer: consumption-based Azure costs (you own the infrastructure). SaaS competitors charge per-document fees that scale linearly with volume. DIY: significant upfront development cost. |
| Time to Production | Weidenhammer: weeks, not months — pre-built accelerator with IaC deployment. DIY: 6–12+ months. SaaS: weeks but with ongoing per-document cost. |
| Customization | Weidenhammer provides custom schemas, white-glove integration, and extensibility via add-on SOWs. SaaS platforms offer configuration within their platform constraints. DIY: unlimited but self-built. |
| Confidence Scoring | Weidenhammer provides dual confidence scoring (field-level + document-level) with configurable thresholds and human-in-the-loop review. Not all competitors offer this granularity. |
| Security & Compliance | Azure Entra ID (SSO + RBAC), deployed in your tenant. SaaS platforms vary — review their SOC 2 and data residency policies. DIY: you manage all security. |
Client Results
Retail Client — Document Processing Transformation
A retail organization processing high volumes of vendor documents deployed Weidenhammer’s AI-Powered Document Processing solution. Within six months:
- Manual data entry reduced by 88%
- 3.5x return on investment achieved
- Processing cycle time reduced from hours to minutes
The solution handled multiple document types across the organization, replacing a fragmented process that previously required a dedicated data entry team.
Document Types We Process
The platform handles any document that contains data your business needs. Common examples by department:
Finance & Accounting
- Invoices and credit memos
- Purchase orders
- Bank statements and remittance advices
- Expense reports and receipts
- Tax forms (W-9, 1099, W-2)
Supply Chain & Logistics
- Bills of lading and shipping manifests
- Packing slips and delivery receipts
- Customs declarations
- Certificates of analysis (COA)
Healthcare
- Explanation of benefits (EOB)
- Medical records and lab results
- Insurance claims and prior authorizations
- Patient intake forms
Insurance
- Claims forms (auto, property, life)
- Policy applications and endorsements
- Loss run reports
- Adjuster reports
Legal & Compliance
- Contracts and amendments
- Regulatory filings
- Certificates of insurance
Manufacturing & Quality
- Inspection reports
- Certificates of conformance
- Material safety data sheets (MSDS)
- Production batch records
Frequently Asked Questions
What types of documents can the solution process?
Any document type that contains semi-structured or non-structured data — invoices, purchase orders, bills of lading, insurance claims, medical records, contracts, certificates of analysis, tax forms, and more. It handles PDFs, Word documents, Excel files, scanned images (PNG, JPEG, TIFF), and mixed-media documents containing text, tables, charts, and handwriting. Custom schemas can be configured for specialized document types unique to your industry.
How is this different from traditional OCR?
Traditional OCR reads characters from an image but doesn’t understand what the data means or where it belongs. This solution uses Generative AI (Azure OpenAI GPT-4o) and Azure AI Content Understanding to not just read the document but interpret its structure, identify which fields map to which data points, and output clean, structured JSON. It adapts to new document layouts without requiring new templates — a fundamental limitation of legacy OCR and template-based tools.
Where does my data go? Is it secure?
Your data stays in your Azure tenant at all times. The entire solution is deployed to your own Azure environment via Infrastructure as Code. Authentication is handled through Azure Entra ID with single sign-on and role-based access control. Your documents and extracted data never pass through third-party infrastructure.
How long does implementation take?
The base platform can be deployed in weeks, not months. Weidenhammer uses a pre-built accelerator deployed via Infrastructure as Code (ARM / Bicep templates and Azure Developer CLI), which eliminates the months-long build cycle of a custom AI project. ERP integration is scoped as a follow-on engagement based on your specific systems and workflows.
What does it cost?
The platform runs on consumption-based Azure pricing in your own tenant — you pay for the compute and AI services you actually use, not a per-document licensing fee. This is a significant cost advantage at scale compared to SaaS competitors that charge per-document fees which grow linearly with your volume. Weidenhammer’s implementation is a fixed-scope engagement.
Does it integrate with my ERP?
Yes. The solution is ERP-agnostic with an API-first architecture. It integrates with Microsoft Dynamics 365, SAP, NetSuite, Oracle, and any system that exposes an API. ERP integration is handled as a dedicated workstream to ensure data mapping, validation rules, and error handling are configured correctly for your specific environment.
What happens when the AI isn’t confident in its extraction?
Every document receives dual confidence scores — field-level and document-level. When scores fall below your configured thresholds, the document is automatically routed to a human review queue in the built-in web interface. Reviewers can validate, correct, and approve extractions before data is sent downstream. This human-in-the-loop design ensures accuracy without creating bottlenecks.
Can I start with one document type and expand later?
Absolutely. Most organizations start with their highest-volume, highest-pain document type — typically invoices or purchase orders — and expand to additional document types over time. Custom schemas for new document types are added as straightforward extensions without re-architecture. This phased approach lets you prove ROI quickly and build internal confidence before scaling.
Engagement Process
Phase 1:
Discovery and Scoping
We assess your current document processing workflows, identify high-impact document types, define initial schemas, and align on integration targets. This phase ensures the solution is configured for your specific business requirements — not a generic deployment.
Phase 2:
Platform Deployment
The AI document processing platform is deployed to your Azure tenant using Infrastructure as Code (Bicep templates). This includes the processing pipeline, web interface, API endpoints, authentication (SSO/RBAC), and monitoring. Deployment is repeatable, auditable, and fast.
Phase 3:
Schema Configuration and Validation
We configure extraction schemas for your target document types and run validation against your actual documents. Confidence thresholds are tuned, edge cases are identified, and the human review workflow is set up and tested.
Phase 4:
Integration and Go-Live
Data routing to your ERP or downstream systems is configured and tested. Email ingestion connectors are set up for your environment. Your team is trained on the review interface, and the solution goes live with production document flow.
Phase 5:
Optimization and Expansion
Post go-live, we monitor extraction accuracy, refine schemas based on real-world performance, and scope additional document types or integrations. Ongoing support is available through Weidenhammer’s Hammer Shield managed services program.
What’s Included
- Azure-native AI document processing platform deployed to your tenant via IaC
- Multi-modal document processing (PDF, Word, Excel, scanned images, mixed media)
- Schema-based extraction with initial set of industry-standard schemas (invoices / POs)
- Dual confidence scoring (field-level + document-level) with configurable thresholds
- Human-in-the-loop review web interface
- API endpoints for downstream integration
- Azure Entra ID authentication (SSO)
- Document split, merge, and batch archive capabilities
- Pagination for large document sets
- Infrastructure as Code deployment (Bicep + Azure Developer CLI)
What’s Not Included (Available as Add-Ons)
- ERP integration (scoped as a separate engagement based on your specific systems)
- Custom schemas beyond the initial set (added as extension SOWs)
- Ongoing managed service and support (available via Hammer Shield)
- Data lakehouse or analytics integration (available as a follow-on engagement)
- Email ingestion connector
- Custom end user roles
Ready to Stop Keying Data by Hand?
Where is manual document processing costing you the most — in labor, in errors, or in time? Schedule a free assessment with Weidenhammer’s Business Platforms & Integration team. We’ll review your current document workflows, identify the highest-impact automation opportunities, and show you how the solution works with your actual documents.