A large enterprise services company was drowning in manual document processing. Their teams spent countless hours reviewing contracts, extracting data, and routing documents, tasks prone to human error and delays.
CodeSwift was brought in to implement AI-powered automation that would transform their document-heavy workflows.
The company processed over 50,000 documents monthly across multiple formats and languages. Existing OCR solutions produced unreliable results, requiring manual verification that negated time savings.
Employees were resistant to automation, fearing job displacement. The solution needed to augment human capabilities rather than replace workers entirely.
We built an intelligent document processing pipeline using large language models for understanding and extraction. The system learns from human corrections, continuously improving accuracy.
Workflow automation routes documents to appropriate teams with extracted data pre-filled, turning reviewers into approvers rather than data entry clerks.
Rollout started with a pilot team processing invoices, then expanded to contracts and legal documents. Human-in-the-loop design ensured quality while building trust in the system.
Regular training sessions helped employees understand and embrace the technology as a tool that made their jobs easier and more strategic.
Manual effort decreased by 70%, with processing time dropping from days to hours. Accuracy improved to 98.5% through continuous learning from corrections.
Employee satisfaction increased as workers shifted from tedious data entry to higher-value review and exception handling tasks.
AI/ML: GPT-4, Claude, custom fine-tuned models
Document Processing: Azure Document Intelligence, Tesseract
Backend: Python, FastAPI, Celery
Database: PostgreSQL, Pinecone (vector DB)
Infrastructure: Azure, Kubernetes
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