Transforming Document Processing with AI Agents
Streamlining document workflows with AI for speed, accuracy, and scale.
The Opportunity
The client, a large organisation handling millions of documents annually, faced significant inefficiencies in document processing workflows. Their operations required extracting key information from multi-format files (PDFs, images, and text), which was time-consuming and error-prone due to reliance on manual methods and outdated tools. The organisation needed an intelligent, automated solution to increase processing speed, reduce costs, and improve data accuracy while maintaining scalability and seamlessly integrating with existing systems.
What we did
✔︎ Designed and deployed an AI Agent: Developed an AI system capable of automating document classification and extracting key information. ✔︎ Created a scalable solution: Ensured the system could process millions of pages daily at high speeds without requiring additional resources. ✔︎ Integrated with existing workflows: Implemented the solution in a way that seamlessly fit into existing operations with minimal disruption. ✔︎ Optimised performance: Tested and refined the AI Agent to ensure reliable and consistent outcomes across diverse file types.
11.5m
pages can be processed daily.
How we did it
We started by assessing the client’s existing document processing pipeline to identify inefficiencies and define clear objectives, focusing on scalability, accuracy, and seamless integration. A centralised platform was developed to allow users to upload documents in various formats, ensuring flexibility for operational needs. To automate data extraction, we integrated a fine-tuned Large Language Model (LLM) capable of processing files autonomously and extracting key information, regardless of document complexity or size. A robust processing pipeline was engineered to manage large-scale workloads, achieving a rate of up to 11.5 million pages in 24 hours. This ensured performance reliability even for extensive documents, such as PDFs exceeding 1,000 pages. We built a customised evaluation suite to rigorously test accuracy and consistency across multiple file types and use cases, ensuring the AI met the highest standards. To optimise processing costs, the workflow was refined to minimise token usage without compromising accuracy, resulting in significant cost savings per document. Finally, the outputs were formatted and seamlessly integrated into the client’s existing operational systems, enabling immediate value realisation with minimal disruption.
