AI Automation - AI Document Processing
We build AI-powered document processing systems that extract, classify, and route information from any document type — turning unstructured data into structured, actionable information.
Intelligent Document Understanding
Every business deals with documents — invoices, contracts, forms, reports, receipts. Manually extracting data from these documents is slow, expensive, and error-prone. OC Imagine builds AI document processing pipelines that read, understand, and extract information from any document format with high accuracy.
Our solutions combine OCR, natural language processing, and custom-trained machine learning models to handle even complex document layouts. Whether you need to process thousands of invoices a day or extract specific clauses from legal contracts, we build systems that do it accurately and at scale.
Why hire us - What sets us apart
We build document processing systems that handle the messy reality of business documents — not just clean, well-formatted samples.
- High accuracy extraction. Custom-trained models that achieve high accuracy on your specific document types, not generic OCR that misreads critical fields.
- Any document format. PDFs, scanned images, handwritten forms, emails, spreadsheets — our systems handle the full range of document types your business receives.
- Validation & compliance. Built-in validation rules that cross-check extracted data against your systems and flag discrepancies for human review.
Our process
- Document analysis. We analyze your document types, identify the data fields you need extracted, and assess the complexity of your processing requirements.
- Model training. We train custom extraction models on your actual documents, iterating until accuracy meets your threshold for each field type.
- Pipeline development. We build the full processing pipeline — ingestion, OCR, extraction, validation, and output — integrated with your existing systems.
- Monitoring & improvement. We deploy with confidence tracking and human-in-the-loop review for low-confidence extractions, continuously improving model accuracy.