Intelligent Document Processing & AI-Powered RPA

AI can now understand, extract, classify, and act on documents—freeing your team from repetitive tasks and errors.

What Is Intelligent Document Processing?

Intelligent Document Processing (IDP) uses AI to automatically extract, structure, and route information from scanned forms, PDFs, emails, spreadsheets, and other unstructured or semi-structured documents.

It typically combines:

Optical Character Recognition (OCR)
Natural Language Processing (NLP)
Machine Learning for classification
Rule-based workflows or Robotic Process Automation (RPA)
Enhances data using additional databases

Why It’s a Core AI Application

Documents drive workflows across every industry—from invoices to contracts
Most document handling today is manual, error-prone, and expensive
IDP is one of the fastest ways to reduce cost and increase compliance
Microsoft provides battle-tested tools to implement it securely and at scale

Microsoft Tools for Intelligent Document Processing

Tool	Role in the IDP Pipeline
Azure Form Recognizer	OCR and pre-trained document parsing (invoices, receipts, IDs)
Azure AI Document Intelligence	Layout and custom extraction models
ML.NET	Train your own classifiers or extractors using C#
Power Automate	Trigger actions based on extracted data
Azure Logic Apps	Build workflows and integrate with enterprise systems
Semantic Kernel	Interpret extracted text and trigger plugins or workflows
SharePoint / OneDrive	Document storage and version control

Common Use Cases for IDP

Workflow Area	Example Use Cases
Finance & AP	Invoice capture, PO matching, payment validation
Legal	Clause extraction, contract risk classification
HR	Resume parsing, onboarding docs, compliance forms
Healthcare	Patient intake forms, insurance claims, medical records, transcribe nurse and doctor consultations
Logistics	Bill of lading, delivery receipts, customs forms
Insurance	Applications, claim forms

Stakeholder Perspectives

🧭 Executives

Cut manual workload in high-volume departments (AP, legal, HR)
Improve compliance, reduce SLA breaches

📋 Business Analysts

Document data fields, accuracy thresholds, exception handling flows
Map which forms are IDP-ready today vs. need redesign

🧑‍💻 Developers

Integrate ML.NET or Form Recognizer with local .NET apps
Use Power Automate or Logic Apps for end-to-end workflow automation

🧾 End Users

Submit a document once—let the system route, verify, and notify automatically

Watch for our book on Intelligent Document Processing

Our upcoming book on IDP will have all the details for executives, managers, business requirements analysts, programmers, and database administrators. We include a C# prototype using Azure Form Recognizer for OCR and layout. You can then add:

ML.NET for document classification or field extraction
Semantic Kernel to interpret extracted content
Power Automate to update records or route documents

Key Features:

Upload a document → receive structured output (JSON or form)
Classify document type
Extract fields like vendor, total, date, and due date
Trigger follow-up action (e.g., approval request, database entry)

Scale to Hundreds of Thousands of Documents

We can scale your IDP system to handle hundreds of thousands of documents, each containing hundreds or even thousands of pages.

Summarize multi-thousand-page documents in minutes
Automatically tag and categorize content at scale
Index long documents so users can jump to relevant sections instantly

Instead of taking hours or days to digest complex material, IDP delivers the insights you need in minutes—accurately, consistently, and at enterprise scale.

Transcribe and Translate at Scale

IDP isn’t just for documents.

Transcribe audio files, including recorded consultations, meetings, or support calls
Translate documents, videos, and audio into other languages using Azure Cognitive Services
Apply the same indexing, tagging, and enrichment workflows across formats

Bring structure to everything—from PDFs and scanned forms to MP4s and WAV files.

Enrich Documents with External Data

Once your documents are converted into structured text, the real intelligence begins.

We can:

Auto-tag and index content
Insert a table of contents into long documents for easier navigation
Enrich content with external databases
- Given a vehicle VIN, return year, make, model, and accident history
- Recognize pharmaceutical names and flag potentially dangerous drug interactions

What was once a pile of paper is now indexed, enriched, and decision-ready data.
Instead of guessing or searching, you act—with context, speed, and confidence.

From Prototype to MVP

Identify 2–3 high-volume document types
Run the prototype using Form Recognizer or ML.NET
Integrate outputs into Power Automate
Build exception-handling workflows
Evaluate: Accuracy, human review rate, time saved

Best Practices

Start with structured forms (invoices, applications, claims)
Use pre-trained models to jumpstart success (Azure Form Recognizer)
Don’t over-optimize—a 90% automation rate can still save hundreds of hours
Include a human-in-the-loop review process for compliance
Document data lineage and audit logs for sensitive workflows

Turn Documents Into Data—and Data Into Action

AI doesn’t just read your documents. It understands them, extracts value, and triggers action.
Let’s build a system that handles paperwork so your people can handle progress.