Rocket Close Slashes Mortgage Document Processing Time by 15x with Amazon Bedrock & Textract (2026)

Rocket Close Slashes Mortgage Document Processing Time by 15x with Amazon Bedrock & Textract (2026)

Rocket Close has dramatically transformed mortgage document processing by integrating Amazon Bedrock and Amazon Textract, achieving a 15-fold reduction in processing time and 90% accuracy in document segmentation, classification, and field extraction. This breakthrough, developed in collaboration with the AWS Generative AI Innovation Center (GenAIIC), marks a pivotal shift in how financial institutions handle the voluminous, unstructured paperwork inherent in home lending.

How Amazon Textract Extracts Data from Mortgage Forms

Amazon Textract, a machine learning service designed to extract text, handwriting, and structured data from scanned documents, serves as the foundational layer for capturing raw content from mortgage applications, pay stubs, tax forms, and bank statements. Unlike traditional OCR tools, Textract preserves document layout and identifies key fields even in complex, multi-page formats—critical for compliance-heavy mortgage workflows.

Why Generative AI Beats Manual Review in Mortgage Underwriting

Prior methods relied on rule-based systems or manual data entry, which were error-prone and slowed approvals by days. With Rocket Close’s AI-driven pipeline, underwriters receive clean, validated data in minutes rather than hours. This acceleration improves customer experience and allows lenders to process higher volumes without proportional increases in staffing or overhead.

How LangChain Enables Adaptive Document Classification

The solution’s adaptability is amplified through integration with LangChain, an open-source framework for orchestrating LLM workflows. This enables Rocket Close’s system to dynamically adjust to evolving document formats and regulatory requirements. It now recognizes new form types, validates cross-field consistency (e.g., income versus debt-to-income ratios), and flags anomalies with minimal human intervention.

Results: 15x Faster Closing Times and 95% Fewer Manual Reviews

Internal testing shows a 95% reduction in manual review hours per loan file, translating to significant cost savings and faster closing timelines. The 90% accuracy rate exceeds industry benchmarks for financial services document processing. Rocket Close is now scaling this solution across its national network, with plans to integrate it into partner networks by the end of the fiscal year.

Why Rocket Close’s Approach Beats Competitors Like Better

While competitors like Better pursue partnerships with OpenAI for decision-making tools, Rocket Close focuses on the upstream challenge: accurate, automated ingestion of documents. Without reliable data extraction, even the most sophisticated AI models cannot function effectively. AWS highlights that Amazon Bedrock Data Automation further streamlines this process by automating insight generation from multimodal content—including images and scanned forms—without additional engineering.

As mortgage origination continues to digitize, Rocket Close’s deployment of Amazon Bedrock and Amazon Textract sets a new standard for efficiency and accuracy in intelligent document processing. The integration exemplifies how enterprise-grade generative AI, when strategically applied, can solve legacy bottlenecks—and redefine what’s possible in regulated industries.