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January 13, 2025 — Today we're introducing Document Intelligence, a new capability now available across our digital workforce platform. After months of development and real-world testing with enterprise clients, we're ready to share what we've learned about automated document processing at scale.
The question we set out to answer was simple: could we eliminate the hours teams spend manually extracting information from documents? Not just speed it up, actually make it disappear.
Turns out, we could.
Across the 1,350+ digital employees we've deployed at enterprise organisations, we noticed a pattern. Different industries, different use cases, but the same underlying bottleneck: valuable information trapped in documents that required manual extraction.
Finance teams reading invoices line by line. Legal departments parsing 20-page contracts for compliance requirements. HR teams manually entering data from identity documents. Customer service operations spending hours after calls documenting what was discussed.
Different contexts, same constraint. Human time spent on repetitive information transfer rather than judgment, analysis, or relationships.
We started asking: what if this extraction work just... happened?
Document Intelligence processes information across any format you throw at it:
Processing approach: The system combines Azure Document Intelligence, advanced OCR, and large language models (Claude 3.5 Sonnet and GPT-4o) to understand context, not just extract text. It creates summaries, pulls specific entities, and answers pre-defined questions about the content.
Output destinations: Extracted data flows wherever you need it, ERP systems, SharePoint, email workflows, Teams, or custom integrations. The workflow adapts to how you already work.
The key insight: you define your extraction requirements once through structured questions. Every document that comes in afterward gets processed automatically against that framework. Consistency at scale, without human intervention.
We're already seeing Document Intelligence in production across multiple enterprise clients. Here's what they're discovering:
The situation: After every group booking call, TUI staff spent roughly an hour filling out intake forms manually. Group size, demographics, destination preferences, duration, special requirements—all typed by hand, every booking.
What changed: Calls get recorded as they normally would. While the conversation happens, Document Intelligence processes the audio. When the call ends, the intake form is already complete and saved to SharePoint.
The result: That hour of administrative work is gone. Staff move immediately to the next customer or focus on complex travel planning that actually needs human expertise. Processing time went from 60 minutes to under 30 seconds per booking.
The situation: When municipalities send contract terms and conditions (typically 20+ pages), Oosterhof's legal team needs to verify compliance with their standards. Questions like: "Is liability properly limited?" "What's the warranty period?" "Does Article 14.2 meet our requirements?" Manual review took hours per document.
What changed: Documents arrive via Teams. Document Intelligence reads them, answers every compliance question, and provides exact citations: "Yes, because Article 14.2 states: [exact text from document]."
The result: Legal team receives completed checklists with source references. They verify in minutes instead of extracting for hours. Their time shifted from data entry to actual legal judgment—the work that requires their expertise.
The situation: Quality assurance teams could only review as many customer service calls as they could manually listen to and score. This created a bottleneck in maintaining quality standards at scale.
What changed: Voice recordings process automatically. Pre-defined quality questions get answered with confidence scores based on conversation analysis.
The result: QA team can now review 10x more calls. Their focus shifted from repetitive scoring mechanics to coaching opportunities and edge case analysis.
One feature has proven particularly important for regulated industries: source citation.
When Document Intelligence answers a question, it doesn't just say "Yes" or "No." It shows you exactly where it found that information in the source document. For legal and compliance teams, this changes everything.
Verification becomes rapid instead of exhaustive. You're not re-reading entire contracts to check the AI's work. You're looking at specific citations to confirm accuracy. What used to take hours now takes minutes.
For audit trails and regulatory requirements, this citation capability means every extracted piece of information traces back to its source. The transparency required for enterprise deployment.
Here's what makes Document Intelligence interesting from an architecture perspective: it's not a separate product. It's a skill that any of our digital employees can apply.
We already have digital employees handling customer service conversations, processing transactions, managing workflows across enterprises. Now they can also process documents.
A digital employee in finance uses Document Intelligence for invoice processing. The same underlying capability powers contract review in legal, identity verification in HR, intake form completion in customer service.
One skill, universal application depending on what the business needs.
This is what we mean by a hybrid workforce. Digital employees that can learn new capabilities and apply them where needed. Humans focusing on judgment, relationships, and complex problem-solving.
The pattern we're seeing is remarkably consistent across sectors:
Financial Services: Invoice processing, bank statement analysis, purchase order reconciliation, payment verification, financial document classification.
Legal & Compliance: Contract review, regulatory document analysis, compliance checklist completion, terms and conditions verification.
Human Resources: Resume parsing, identity document verification, onboarding documentation, background check processing.
Healthcare: Patient intake forms, insurance verification, medical record processing, clinical documentation.
Customer Operations: Call transcription and summarization, quality assurance scoring, intake form completion, feedback analysis.
Different industries, but the underlying need is identical: structured information extraction from unstructured sources.
Document Intelligence delivers 99%+ accuracy through a multi-model approach:
Azure Document Intelligence: Pre-trained on millions of documents, provides baseline understanding and structure recognition across document types.
Advanced OCR: Handles difficult-to-read scanned documents through contrast optimization and intelligent preprocessing.
Large Language Models: Claude 3.5 Sonnet and GPT-4o provide contextual understanding. They don't just extract text—they understand what the text means in context.
Validation Layers: Automated verification through regex patterns, fuzzy matching, and business rule validation ensures accuracy at scale.
Processing speed: Under 30 seconds for standard documents. Voice recordings processed in near-real-time.
Supported languages: 45+ languages through Azure Document Intelligence.
Security: All processing occurs within ISO 27001 and GDPR-compliant infrastructure. Documents never leave secure environments.
Document Intelligence is available now for enterprise clients. Typical deployment takes 2-4 weeks, including:
Integration options include REST APIs, webhook callbacks, direct system connectors, SharePoint, Teams, and email workflows.
Our pricing follows the same outcome-based model we use across the platform: you pay for documents processed or workflows completed, not licensing fees or seat counts.
We're facing a structural workforce challenge globally. Aging populations, declining birth rates, persistent labor shortages. The traditional answer of "hire more people" isn't going to solve this mathematically.
But here's what we keep discovering: a lot of what we call "work" isn't actually the valuable part. The valuable part is the judgment, the relationships, the creative problem-solving, the strategic thinking.
The extraction, the data entry, the form filling, the repetitive verification—that's mechanics. Important mechanics, but mechanics nonetheless.
What we're exploring with Document Intelligence and our broader digital workforce platform is a different question: what could work look like if the mechanics just happened automatically? Not what work should look like, but what it could look like.
When document processing happens in the background, teams start asking different questions. Not "How can we process these faster?" but "What becomes possible if processing isn't a constraint?"
Legal teams reviewing 10x more contracts because they're verifying analysis instead of extracting data. Travel companies handling more bookings with existing staff because administrative work disappeared. QA teams maintaining standards across 100% of interactions instead of random sampling.
The compound effects are interesting. When you eliminate one bottleneck, you discover the next opportunity.
With 1,350+ digital employees already deployed across enterprise operations, Document Intelligence represents an expansion of what autonomous work actually means.
We started with conversational AI and workflow automation. Now we're adding document intelligence. Next will be additional capabilities that handle other categories of repetitive work.
The question we're exploring with our clients: as we eliminate more categories of manual work, what does the workweek start to look like?
Not as a theoretical exercise, but as a practical reality unfolding in production environments right now.
We're calling this exploration "Make Friday a Freeday" not as a slogan, but as a genuine question about what becomes possible when digital and human workforces operate together effectively.
If your teams are spending significant time on document processing, information extraction, or form completion, we should explore what Document Intelligence could look like in your specific context.
We're not selling a product. We're exploring what becomes possible when this constraint disappears. What your team's workweek could look like. What opportunities emerge when administrative extraction happens automatically.
We're learning this in real-time with enterprises across finance, travel, legal, healthcare, and manufacturing. The patterns are emerging, and they're compelling.
