What We Build
We build end-to-end document processing pipelines that automatically extract, categorize, and structure data from your business-critical documents. Our systems combine:
- Multi-stage prompting methodology - Initial extraction followed by validation and refinement for maximum accuracy
- Structured outputs - Clean, validated JSON data ready for integration with your existing systems
- Human-in-the-loop workflows - Strategic checkpoints where accuracy matters most, ensuring confidence in automated results
- Reusable architecture - Built to scale across multiple document types with minimal reconfiguration
Unlike generic OCR or extraction tools, we build custom pipelines tailored to your specific document types, business rules, and accuracy requirements.
How It Works
Our proven document processing approach follows a systematic methodology:
Stage 1: Initial Extraction
Advanced language models analyze your documents to identify and extract key fields, relationships, and data points. This stage focuses on comprehensive capture, ensuring no critical information is missed.
Stage 2: Validation & Refinement
A second pass validates extracted data against business rules, cross-checks for consistency, and applies domain-specific logic. This two-stage approach dramatically improves accuracy over single-pass extraction.
Stage 3: Human Review (Where It Matters)
Strategic human-in-the-loop checkpoints focus expert review where it's most valuable. Rather than reviewing every document, your team validates edge cases and trains the system to handle similar scenarios automatically in the future.
Stage 4: Integration & Delivery
Structured data flows seamlessly into your databases, CRMs, accounting systems, or data warehouses. We handle the integration work so extracted data is immediately actionable.
Our Approach
Discovery & Assessment
We evaluate your document type, accuracy requirements, and processing volume to determine feasibility and ROI before any major investment.
- Document type analysis and sample review
- Accuracy requirement definition
- Volume and throughput assessment
- ROI calculation and recommendation
Proof of Concept
We build a working system for your document type, demonstrating real-world accuracy on your actual documents.
- Custom extraction logic for your document type
- Two-stage prompting implementation
- Accuracy testing on sample dataset
- Human-in-the-loop workflow design
- Working demo using your real documents
Production Deployment
We scale your POC to production-ready infrastructure with full integration into your existing systems.
- Production infrastructure and scaling
- Database and API integration
- Batch processing and queue management
- Error handling and monitoring
- User training and documentation
Ongoing Support
Continuous improvement, monitoring, and expansion to additional document types as your needs grow.
- System monitoring and maintenance
- Accuracy refinement and prompt tuning
- Additional document type integration
- Feature enhancements and optimization
Case Study: SegTax Settlement Statements
The Challenge
SegTax needed to process hundreds of real estate settlement statements to extract and categorize line items for tax reporting. These documents varied significantly in format, contained complex financial calculations, and required high accuracy for regulatory compliance.
The Solution
We built a two-stage document processing pipeline that:
- Extracted all line items with associated amounts and descriptions
- Categorized each item according to SegTax's proprietary taxonomy
- Validated calculations and flagged discrepancies
- Structured output for seamless database integration
The Results
- 90%+ extraction accuracy on complex, varied document formats
- 75% reduction in manual review time through intelligent automation
- Scalable architecture ready for multiple additional document types
- Rapid production deployment from initial concept to working system
The Testimonial
"Ben integrated the ChatGPT API into our platform to extract data from unstructured settlement statement pdfs. This required diving into the complex domain of real estate accounting and using artificial intelligence to extract, categorize, and produce structured data from this unstructured data source of PDF with varying formats. I was impressed with Ben's ability to build a PoC quickly - iterate on feedback and then integrate a usable solution into our production software stack. Also Ben has a great attitude and is fun to work with." - Joe Acanfora, Segtax Co-Founder
Industries & Document Types
Our document processing pipeline architecture is proven and reusable across industries and document types:
Real Estate
- Settlement statements (HUD-1, ALTA)
- Deeds and title documents
- Property tax assessments
- Lease agreements
- Inspection reports
Tax & Accounting
- Tax forms (1099s, W-2s, K-1s)
- Receipts and expense reports
- Financial statements
- Bank statements
- Invoices and bills
Legal
- Contracts and agreements
- Discovery documents
- Court filings
- Legal correspondence
- Due diligence documents
Healthcare
- Medical records
- Insurance claims (EOBs)
- Prior authorization forms
- Lab reports and results
- Patient intake forms
Finance
- Loan applications
- Credit reports
- Bank statements
- Investment documents
- Financial disclosures
Government
- Permits and licenses
- Public records
- Compliance documents
- Grant applications
- Regulatory filings
Why Choose Our Approach
- Proven methodology - Two-stage prompting with human-in-the-loop has delivered 90%+ accuracy in production
- Speed to value - See working results quickly, not months of custom development
- Risk mitigation - Discovery phase determines feasibility before major investment
- Reusable patterns - Efficient expansion across multiple document types as your pipeline grows
- Scalable architecture - Built to handle increasing volume and document variety
- No vendor lock-in - We use open standards and can integrate with your existing tech stack
Ready to Transform Your Document Processing?
Start with a free 30-minute Document Processing Assessment to determine if automation is right for your use case.
We'll discuss your document types, volume, accuracy requirements, and provide honest feedback on whether our approach is a good fit.