Demystifying Intelligent Document Processing
Across sectors like manufacturing, finance, and healthcare, enterprises wrestle daily with a flood of unstructured documents—ranging from contracts and financial statements to patient referrals and supply chain forms. Historically, extracting insight from these documents has been manual, slow, and error-prone.
That’s changing fast.
Intelligent Document Processing (IDP), powered by AI and ML, is transforming how organizations extract, structure, and act on unstructured data.
Why It Matters
- Manufacturers are streamlining POs, invoices, and supplier compliance.
- Financial institutions are accelerating onboarding, loan approvals, and regulatory reporting.
- Healthcare providers are improving patient intake and claims processing.
- Legal teams are automating contract review and risk analysis.
- Government agencies are digitizing citizen services—from benefits to permits.
The results?
Faster processing. Fewer errors. Greater compliance. Lower costs. Better experiences. But the benefits go beyond efficiency: IDP becomes a strategic wedge into enterprise AI adoption. Document workflows are often already well-defined and data-rich, making them ideal entry points for GenAI-powered transformation.
Industry-Specific Use Cases for GenAI-Powered IDP
- Government – Process citizen applications, immigration forms, and legal contracts faster, with fewer errors.
- Healthcare – Extract patient demographics, history, and referrals for quicker care planning.
- Finance – Automate loan applications, KYC, tax forms, and filings to reduce cycle times.
- Logistics – Reconcile invoices, extract PO data, and reduce supply chain delays.
- Retail/Ecommerce – Automate catalog updates, customer orders, and marketing asset tagging.
With generative models via Amazon Bedrock, and foundational ML services like Amazon Textract and Comprehend, organizations are unlocking hidden value in documents once considered unmanageable.
Let’s look at two real-world examples.
1: Audi Automates Tender Matching with GenAI
Audi set out to overhaul its labor-intensive tendering process. With over 1,000 tenders and 20,000+ offers annually, engineers were spending 800,000+ hours per year manually comparing documents.
Challenge
- 400+ page tender documents
- Inconsistent supplier formats
- Manual Excel workflows
- SME fatigue and fear of replacement
Solution
A GenAI-powered platform combining LLMs, semantic search, and human oversight:
- Preprocessing with AWS Textract and layout-aware chunking
- Requirement extraction via LLMs, reviewed by SMEs
- Semantic matching using Titan embeddings
- Evaluation with LLM-generated scores and human-reviewed rationales
Tech Stack
AWS Textract, Bedrock (Claude & Titan), Step Functions, Lambda, Aurora Postgres + pgvector
Custom UI for SMEs with document syncing, auto-highlights, and scoring.
Outcomes
- Thousands of hours saved
- Accelerated evaluations
- Strong SME buy-in via user-centered design
- Fine-tuned retrieval models underway
Executive Takeaways
- Efficiency with Control – Automates tedious work while preserving expert judgment
- Scalable Architecture – Serverless, low-ops, built on AWS
- Adoption-First – SME engagement drove successful rollout
- Tuning for Impact – Retrieval quality is the GenAI differentiator
Audi shows how GenAI can scale real business outcomes without compromising the human element.
2: Forcura Streamlines Patient Referrals with Amazon Bedrock
Forcura, a HITRUST-certified healthcare workflow provider, used Claude 3 via Amazon Bedrock to build a referral summarization feature. The goal: help clinicians quickly act on massive, complex referral packets—often hundreds of pages long.
Challenge
- Clinicians struggled to extract key data
- Referral delays impacted care quality and compliance
- Early concerns around GenAI accuracy
Solution
- Referral summarization using Claude 3
- Secure storage in Amazon S3
- Human-in-the-loop validation with clinicians
Tech Stack
Amazon Bedrock (Claude 3), Amazon S3
Fully integrated into Forcura’s AWS-native platform.
Outcomes
- Production feature built in <90 days
- Adopted by 10 clients within 1 month
- Supporting 900+ providers and 1M+ patients
- Trust earned through human validation
Executive Takeaways
- Rapid Delivery – Live in under 3 months
- Trust Built In – Human review resolved skepticism
- Operational Leverage – Handled volume without adding headcount
- Future-Proofed – Bedrock enables seamless model evolution
Forcura’s success highlights the power of pairing GenAI with thoughtful UX, security, and feedback loops in regulated industries.
3: Automating HOA Document Parsing and Data Extraction
Overview
A leading property management technology firm leveraged GenAI to streamline how it extracts structured data from Homeowners Association (HOA) documents. These documents—often unstandardized and filled with dense legal language—contain key facts (e.g., dues, pet restrictions, parking rules) that need regular updating in internal systems.
Challenge
- HOA docs vary widely in structure and length
- Manual data extraction was inconsistent and slow
- Key information often buried in dense or ambiguous legal text
- Human oversight required for accuracy and liability
Solution
An IDP pipeline using GenAI to extract answers to predefined structured data fields:
- Document parsing via LLMs with domain-specific prompt tuning
- Highlight + reference system allowing SMEs to trace extracted answers back to source text
- Human-in-the-loop UI for review, correction, and final approval
Tech Stack
Amazon Bedrock (Claude or Titan), AWS Lambda, Amazon S3
Custom UI for reviewers with citation linking and structured form controls
Outcomes
- Reduced time spent per document by over 70%
- Higher accuracy and consistency across properties
- Full auditability through citation-based validation
- Trusted adoption due to clear human approval checkpoints
Executive Takeaways
- Human-Centered AI – AI does the heavy lifting, humans stay in control
- Structured Data at Scale – Turns unstructured PDFs into normalized, actionable data
- Traceable Outputs – Embedded references build trust and enable audits
- Low-Lift Implementation – Easily integrates with existing property management systems
This HOA-focused IDP use case shows how even niche, operationally specific document types can be transformed using GenAI—enhancing speed, consistency, and trust in high-volume, high-variability workflows.
Kickstart Your IDP Journey with GenAI
At Allata, we help organizations unlock the full potential of their document workflows using AWS-native, AI-driven solutions.
We deliver:
- Faster, more accurate document processing
- Seamless integration with systems like EHR, ERP, CRM, and case management
- Secure, scalable, and cost-effective automation
- Actionable insights through advanced analytics
Let’s explore how GenAI-powered IDP can improve efficiency, compliance, and experience—without adding complexity.
Contact us to start your IDP journey with Allata and AWS.
