Document Intelligence Hub

Our client, a regional legal services provider with seventy-five attorneys across four offices, was spending an estimated twelve thousand billable hours per year on routine document review. Incoming filings, contracts, and regulatory submissions arrived in a mix of formats, including scanned PDFs, Word documents, and email attachments, requiring paralegals to manually read, categorize, and route each one to the appropriate practice group.

The volume was staggering. The firm processed an average of three hundred documents per business day, and the manual pipeline created bottlenecks that delayed client responses by an average of forty-eight hours. Senior partners were frustrated that highly trained attorneys spent hours on classification tasks that added no analytical value, and the firm was losing competitive bids partly because of slower turnaround times.

The firm had experimented with basic keyword search tools, but the nuance required for legal document classification, where a single clause can change the entire meaning and routing of a filing, demanded a more sophisticated approach. They engaged STC to design and deploy an intelligent document processing system that could handle the complexity of legal language while maintaining the accuracy standards their practice demanded.

The document intelligence pipeline was designed with the unique demands of legal practice in mind. The OCR engine was calibrated specifically for legal document types, handling everything from court filings with numbered paragraphs to multi-party contracts with nested exhibit references. We implemented a confidence-scored output system where every extraction and classification decision comes with a transparency layer showing the model's reasoning.

The NLP classification models were fine-tuned using a curated training set assembled in collaboration with the firm's senior attorneys. Rather than relying on generic legal language models, we built domain-specific classifiers that understand the firm's particular practice terminology, filing conventions, and jurisdictional variations. The system supports continuous learning, automatically incorporating corrections from the human review loop into weekly model retraining cycles.

Integration with the firm's existing document management system was accomplished through a secure API layer that maintains full chain-of-custody tracking. Every document's journey, from ingestion through classification to attorney assignment, is logged with timestamps and audit trails that satisfy the firm's compliance requirements.