Built Technologies, a real estate finance software provider managing over $500B in project volume, has deployed an AI-powered document intelligence engine on AWS to automate complex, high-volume document processing. The solution replaces traditional manual workflows by utilizing Amazon Bedrock and the AWS Intelligent Document Processing (IDP) Accelerator to classify, extract, and reason over more than 250 document types. By moving from simple text extraction to context-aware document understanding, the company aims to support a growing suite of agentic products across the real estate finance lifecycle.

Previously, the firm relied on traditional OCR (technique for converting scanned images into machine-readable text) and standard machine learning to process documents. While effective for predictable layouts, this approach struggled with the high variability of real estate finance documentation, which often includes nested tables, inconsistent formats, and domain-specific legal language. The new system is designed to maintain over 95 percent confidence in classification and extraction tasks, enabling it to handle complex documents that may exceed 500 pages in length.

The architecture centers on a multi-stage pipeline orchestrated by AWS Step Functions, which parallelizes the processing of individual document sections to reduce turnaround times from days to minutes. A React-based user interface, secured via Amazon Cognito, allows both technical teams and subject matter experts to manage schemas, review results, and inspect confidence scores. The pipeline leverages Amazon Textract for foundational document structure and Amazon Bedrock for generative AI reasoning. To manage scale, the system uses a concurrency layer composed of Amazon DynamoDB and Amazon SQS (managed message queuing service), ensuring stable performance across both single ad hoc uploads and batch operations involving thousands of documents.

This horizontal capability is currently in production for commercial construction loan draw packages, but the architecture is reusable for other agentic workflows. Future applications include agents specialized in loan agreements, insurance certificate validation, underwriting, asset management, and regulatory compliance. By decoupling the document intelligence layer from specific product workflows, Built Technologies can iterate on its AI roadmap without reconstructing extraction pipelines for each new use case. The platform also employs caching mechanisms for prompts within Amazon Bedrock to improve efficiency when processing high volumes of standardized document classes.

Built Technologies, a real estate finance software provider managing over $500B in project volume, has deployed an AI-powered document intelligence engine on AWS to automate complex, high-volume document processing. The solution replaces traditional manual workflows by utilizing Amazon Bedrock and the AWS Intelligent Document Processing (IDP) Accelerator to classify, extract, and reason over more than 250 document types. By moving from simple text extraction to context-aware document understanding, the company aims to support a growing suite of agentic products across the real estate finance lifecycle.

Previously, the firm relied on traditional OCR (technique for converting scanned images into machine-readable text) and standard machine learning to process documents. While effective for predictable layouts, this approach struggled with the high variability of real estate finance documentation, which often includes nested tables, inconsistent formats, and domain-specific legal language. The new system is designed to maintain over 95 percent confidence in classification and extraction tasks, enabling it to handle complex documents that may exceed 500 pages in length.

The architecture centers on a multi-stage pipeline orchestrated by AWS Step Functions, which parallelizes the processing of individual document sections to reduce turnaround times from days to minutes. A React-based user interface, secured via Amazon Cognito, allows both technical teams and subject matter experts to manage schemas, review results, and inspect confidence scores. The pipeline leverages Amazon Textract for foundational document structure and Amazon Bedrock for generative AI reasoning. To manage scale, the system uses a concurrency layer composed of Amazon DynamoDB and Amazon SQS (managed message queuing service), ensuring stable performance across both single ad hoc uploads and batch operations involving thousands of documents.

This horizontal capability is currently in production for commercial construction loan draw packages, but the architecture is reusable for other agentic workflows. Future applications include agents specialized in loan agreements, insurance certificate validation, underwriting, asset management, and regulatory compliance. By decoupling the document intelligence layer from specific product workflows, Built Technologies can iterate on its AI roadmap without reconstructing extraction pipelines for each new use case. The platform also employs caching mechanisms for prompts within Amazon Bedrock to improve efficiency when processing high volumes of standardized document classes.