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Your team manually keys data from documents into your system every day?
Documents arriving in different formats making consistent extraction impossible?
AI Document Intelligence Services
Documents contain business-critical data that your systems can't reach. Invoices, contracts, forms, reports, and scanned records -- the information is there, but it's locked in unstructured formats that require human eyes to read and human hands to enter.
AI document intelligence combines OCR, large language models, and structured extraction pipelines to read any document, extract the fields that matter, validate the output, and deliver clean data to your systems -- without human data entry.
AI-powered reading of any document format -- PDF, scan, image, email attachment
LLM-based extraction for complex or semi-structured documents where context matters
Structured output delivered to your ERP, database, or API with validation built in
Built production OCR and AI extraction systems for manufacturing and industrial use
Trusted by startups & global brands worldwide
Documents are the last manual step in automated workflows
Most business workflows are partially automated. Data flows between CRM, ERP, and databases via APIs. But somewhere in the process, a human is reading a PDF and typing what they see into a system. That step scales linearly -- more volume means more headcount, more errors, and more delay.
AI document intelligence removes that step. The document arrives, the system reads it, the data lands in your system -- validated and structured, ready to use.
We built a production AI OCR system for gas station fuel delivery invoices -- thousands of invoices a month, different formats, processed automatically with structured output delivered to the operator's management system. The same technology applies to your document workflow.
For end-to-end invoice processing automation -- from extraction through ERP posting and approval routing -- see our dedicated service. For broader business process automation that includes document workflows as one step in a larger process, we scope the full picture.
What we build
Document OCR and reading
AI-powered reading of PDFs, scanned images, photos, and digital documents. Pre-processing for low-quality scans -- deskewing, contrast enhancement, noise removal. Multi-page document handling with page classification. Table extraction for line-item data in invoices and forms. The text layer that everything else is built on.
LLM-based field extraction
Large language model extraction for documents where field locations and labels vary across templates. Understanding of context, inferences, and relationships -- not just position matching. Extraction of complex fields like payment terms, jurisdiction clauses, or conditional amounts. Handles the document variation that breaks rule-based systems.
Document classification
AI that reads incoming documents and classifies them by type before routing to the appropriate extraction pipeline. Invoices to AP, contracts to legal, applications to onboarding, support attachments to the right queue. Classification confidence scoring with fallback to human review for ambiguous documents.
Validation and quality control
Business rule validation on extracted data -- format checks, range checks, cross-field validation, and lookup against reference data. Confidence scoring for each extracted field. Low-confidence or failed extractions routed to exception queue. Corrections feed back into extraction models. The quality layer that makes extracted data trustworthy enough to post automatically.
Exception review workflow
Review interface where operators handle flagged extractions. Original document and extracted fields displayed side by side. Guided correction with field-level feedback. Correction submission that feeds back into training data. Processing metrics and exception rate dashboards. The human-in-the-loop that keeps the system accurate as document formats evolve.
Data delivery and integration
Structured output in the format your downstream systems need -- JSON for APIs, SQL writes for databases, XML for ERP systems, CSV for data platforms. We design the output schema to match your target data model exactly. Delivery can be triggered by document arrival, on a schedule, or via webhook. The integration layer that gets extracted data where it needs to go.
Tell us which document type costs your team the most time.
We'll design the extraction system and give you a fixed cost.
How we work
We audit your document types -- formats received, volume per type, current extraction method, and error rates. We identify which documents are high-volume and consistent (rule-based extraction wins here) and which are variable (LLM-based extraction wins here). You get a scoped system design before any code is written.
Document type inventory and format analysis
Volume measurement per source and channel
Current extraction method and error rate baseline
Extraction approach recommendation per document type
Ready to eliminate manual document data entry?
Tell us your document types and volumes. We'll design the extraction pipeline and give you a fixed cost with a straight-through processing rate estimate.
What our clients say
Case studies
USA
CanadaRelated services
Invoice Processing Automation — End-to-end AP automation from invoice extraction through ERP posting and payment
Data Extraction Automation — Extract structured data from websites, databases, and APIs at scale
Document Automation — Automated generation, routing, and approval of outbound documents
Business Process Automation — Automate the full workflow where document extraction is one step in a larger process
OCR Development — Custom OCR systems for industry-specific document types and scanning environments
Eliminate manual document data entry.
Tell us your document types and processing volume. We'll design the extraction pipeline and give you a fixed cost.
Frequently asked questions
AI document intelligence is the combination of optical character recognition (OCR), large language model (LLM) extraction, and structured data pipelines to automatically read documents and extract information into usable data. Traditional OCR reads text from images and PDFs but produces raw text -- not structured fields. AI document intelligence goes further by understanding the meaning and context of extracted text, classifying documents by type, mapping fields to your target data schema, and validating output against business rules before it reaches your system.
We build systems for: invoices and purchase orders (extracting vendor, line items, totals, and tax), contracts and agreements (extracting parties, dates, terms, and key clauses), forms and applications (extracting field values from structured forms regardless of layout variation), shipping and logistics documents (bills of lading, packing lists, delivery notes), identity documents (passports, driving licences, ID cards for KYC), medical and clinical documents (lab reports, prescriptions, referral letters), and industry-specific documents (certificates, inspection reports, warranty claims). The AI approaches each document type differently based on its structure and the extraction requirements.
Traditional OCR reads text and produces a text string. Rule-based extraction then tries to find fields by position or pattern -- it breaks when the document layout changes. LLM-based extraction reads the document as a language model would -- understanding context, inferences, and relationships between fields. It can extract "the total amount excluding VAT" from a document where it's described in several different ways across different vendor templates. It handles variation that breaks rule-based systems. We use LLMs for complex or variable documents and rule-based extraction for high-volume, consistent document types where speed and cost matter more than flexibility.
For high-quality digital PDFs and consistent document types, accuracy is typically 95--99%. For scanned documents, accuracy depends on scan quality. We improve accuracy through document pre-processing (image enhancement, deskewing), vendor-specific templates for high-volume document sources, confidence scoring that flags low-confidence extractions for human review, and validation rules that cross-check extracted values against expected formats, ranges, and business rules. Most production systems reach 80--95% straight-through processing rates -- meaning only 5--20% of documents require any human review.
Every production document intelligence system has an exception path. Low-confidence extractions and documents that fail validation are routed to a human review queue. Reviewers see the original document and the extracted fields side by side, correct any errors, and confirm the extraction. Corrections feed back into the system to improve future accuracy for similar documents. The exception queue is designed to minimise review time -- a reviewer typically handles an exception in under 60 seconds.
A focused document extraction system -- one document type, validation rules, and output delivery to one target system -- typically runs $25,000--$60,000. Multi-document type platforms with complex extraction logic, exception workflows, and multiple output integrations run $60,000--$150,000. We've built production OCR and AI extraction systems including a gas station fuel delivery invoice system. We scope every project before pricing it.