We build systems that read, understand, and extract structured data from any document type, eliminating manual data entry and accelerating business processes.
Businesses run on documents: invoices, contracts, purchase orders, receipts, medical records, insurance claims, and more. Yet most of this information is trapped in unstructured formats that require manual reading, interpretation, and data entry. This creates bottlenecks, introduces errors, and consumes skilled employee time on repetitive tasks that add little value.
Traditional OCR and template-based extraction tools handle standardized documents with fixed layouts, but they fail when confronted with the variety of real-world documents. Different vendors use different invoice formats. Contracts vary in structure and terminology. Forms arrive in multiple languages and qualities. The volume and variability of documents in most organizations make rule-based approaches impractical to maintain.
AI-powered document processing changes this equation fundamentally. By combining computer vision, natural language understanding, and large language models, modern document AI systems can process documents as flexibly as a human reader while operating at machine speed and scale. Arthiq has built this capability into our InvoiceRunner product and delivers the same technology to clients across industries.
Arthiq builds document processing pipelines with multiple AI stages, each optimized for a specific aspect of document understanding. The pipeline begins with document ingestion and preprocessing that handles format conversion, image enhancement, and page segmentation. Documents arrive via email, upload, API, or file system monitoring, and the system processes them regardless of source.
The classification stage identifies the document type and routes it to the appropriate extraction pipeline. Our classifiers handle hundreds of document categories with over 95 percent accuracy, and they learn new categories from labeled examples without requiring retraining of the entire model. For organizations processing many document types, this automated routing eliminates the need for manual sorting.
The extraction stage uses a combination of layout analysis, OCR, and LLM-based comprehension to identify and extract data fields. Unlike template-based systems that require per-format configuration, our LLM-powered extraction understands document semantics and adapts to format variations automatically. We validate extracted data against business rules, cross-reference with existing records, and flag discrepancies for human review.
Real-world document processing involves scenarios that stump simpler systems. Arthiq builds solutions that handle multi-page documents, tables that span pages, handwritten annotations, mixed-language content, and poor-quality scans. Our preprocessing pipeline enhances image quality, corrects skew and orientation, and separates multi-document scans into individual documents before processing.
For documents with complex tabular data like financial statements or detailed invoices, we use specialized table extraction models that understand row and column relationships even when borders are missing or cells span multiple rows. The extracted tables are converted to structured formats that integrate directly with your downstream systems.
We also handle document relationships. A purchase order references a contract. An invoice references a purchase order. A payment references an invoice. Our systems track these relationships and perform cross-document validation that catches errors before they propagate through your business processes.
Document processing is rarely an end in itself. The value comes from what happens with the extracted data. Arthiq builds end-to-end pipelines that connect document processing to downstream business systems. Extracted invoice data flows into your accounting system. Contract terms populate your CLM platform. Customer forms update your CRM. The entire chain from document receipt to system update runs automatically.
We implement approval workflows for extracted data that require human verification. Reviewers see the original document alongside extracted data, with highlighted regions showing where each field was found. This makes verification fast and accurate, and reviewer corrections feed back into the system to improve future extraction accuracy.
For high-volume environments, our systems process thousands of documents per hour with horizontal scaling that matches your throughput requirements. We provide real-time dashboards showing processing volumes, extraction accuracy, exception rates, and processing times, giving you full visibility into the pipeline performance.
Arthiq has deep expertise in document AI, proven through our own InvoiceRunner product and numerous client implementations. We understand the practical challenges of document processing in production and build systems that are reliable, accurate, and maintainable.
Our approach starts with a sample of your actual documents. We benchmark extraction accuracy against your requirements, identify any document types that need special handling, and design a pipeline architecture that meets your throughput and accuracy targets. Development proceeds in focused sprints with regular accuracy benchmarks.
Contact us at founders@arthiq.co to discuss how Document AI can eliminate manual data entry in your organization and accelerate your document-dependent business processes.
Our team will build an intelligent document processing pipeline that eliminates manual data entry and accelerates your document-dependent workflows.