AI Document Processing Engineers for Production Pipelines
No Vibe Coding. We build intelligent document processing systems that handle real-world documents: scanned invoices, complex contracts, multi-column PDFs, and handwritten forms. Our senior engineers understand every extraction decision, every accuracy trade-off, every line of code we ship.
Built With
Recognized by Clutch
What We Build with Document AI
From OCR pipelines to multi-modal LLM extraction, we deliver document automation systems that work on your actual documents, not just clean demos.
Intelligent Document Processing Pipelines
End-to-end IDP systems that classify, extract, and validate data from unstructured documents at scale. We combine OCR engines with AI validation layers so your pipelines handle real-world documents: scans at odd angles, low-resolution images, mixed fonts, and partially filled forms.
Multi-Modal LLM Parsing
We use GPT-4 Vision, Claude Vision, and Gemini Vision to extract structured data from documents that defeat traditional OCR: multi-column layouts, nested tables, handwritten annotations, charts embedded in PDFs, and mixed text and image content.
Invoice and Receipt Automation
Accounts payable and receivable automation that reads invoices from any vendor, maps fields to your GL codes, and pushes validated data into your ERP. We handle hundreds of vendor formats without brittle template matching, using AI extraction that generalizes across layouts.
Contract and Legal Document Analysis
AI pipelines that read contracts and surface what matters: key clauses, obligations, dates, parties, and risk signals. Legal and compliance teams get structured extracts and flagged items instead of manually reading hundreds of pages per deal.
Form Processing and Digitization
Automated digitization of paper and digital forms from government, healthcare, and financial services. We build extraction pipelines that handle checkboxes, free-text fields, signatures, and structured tables, then validate outputs against your business rules before writing to downstream systems.
RAG over Document Corpora
Retrieval systems that let your team query large document libraries in plain language and get sourced, accurate answers. We handle ingestion pipelines, chunking strategies, hybrid search, and access controls so users only retrieve documents they are authorized to see.
Why Senior Engineers Matter for Document AI Projects
Document processing looks deceptively simple in demos. You pass a clean PDF to an API and get structured JSON back. Then you run it on your actual document library: scans from 2009, invoices with watermarks, contracts with tables that span three pages, forms where vendors put the total in different places every quarter. The demo falls apart immediately.
Production document pipelines require engineering decisions that tutorials never cover. Which extraction approach handles your specific document types most accurately? How do you benchmark accuracy before committing to a technology? What validation logic catches the 3% of extractions that are confidently wrong? How do you build a human review workflow that does not create a new bottleneck? How do you handle documents that arrive as email attachments, SharePoint uploads, and API calls simultaneously?
We have shipped document processing systems that handle millions of documents per month across invoice automation, contract analysis, and regulatory filing extraction. We know which OCR engine performs best for which document type, how to tune vision LLMs for structured extraction, and how to build pipelines that degrade gracefully when document quality is poor rather than silently producing wrong data.
Our Tech Stack
We work across the full document AI ecosystem and select tools based on your document types, accuracy requirements, and compliance constraints.
Document AI Projects We Have Delivered
Real results from production document processing deployments.
AI Sales Assistant with RAG
Built a document ingestion pipeline that processed thousands of product specs, contracts, and datasheets into a retrieval system. The sales assistant queries this corpus in real time to give accurate, sourced answers during live customer interactions.
Read Case StudyE-Learning Content Generation
Designed an automated pipeline that ingests curriculum documents, extracts structured knowledge from PDFs and Word files, and generates validated learning content. The system processes complex educational materials with tables, diagrams, and cross-references.
Read Case StudyMulti-Agent Document Workflows
Built a multi-agent system where specialized agents handle document classification, data extraction, validation, and routing. Each agent is accountable for a specific stage of the pipeline, enabling parallel processing and clear error attribution.
Read Case StudyHow We Work
A straightforward process from first call to production deployment.
Discovery Call
We start with a 30-minute technical conversation to understand your documents, your data quality, and your downstream systems. We ask about volume, formats, edge cases, and compliance requirements. No sales pitch.
Architecture Proposal
Within a week, we deliver a detailed proposal: extraction approach, technology choices with rationale, accuracy benchmarks we will target, and integration plan for your existing systems. You see exactly what we plan to build and why.
Build and Ship
We build iteratively, starting with your highest-volume document type and expanding from there. You get weekly demos of working extraction pipelines, accuracy reports against your real documents, and continuous knowledge transfer to your team.
Frequently Asked Questions
Ready to Automate Your Document Workflows?
Tell us about your documents and we will respond within 24 hours with an initial assessment. No commitment, no pressure, just a technical conversation about what extraction accuracy is realistic for your document types.
Get a Free Assessment
Describe your document types and automation goals and we'll send you an initial technical assessment within 24 hours.