The customer managed tens of thousands of handwritten, scanned, and unstructured legal documents that required manual classification and validation. Processing was slow, error-prone, and impossible to scale as demand grew.
The objective was to implement a scalable Generative-AI IDP solution to automate the extraction, classification, and validation of complex legal documents. The customer needed to reduce delays, improve accuracy, and support rapid onboarding of new clients.
The manual process drove high operational costs, slowed revenue due to long processing cycles, introduced compliance risks, and prevented the customer from onboarding new clients or expanding services.
The customer needed an automated, reliable, and scalable IDP system to classify documents, extract key data, ensure compliance, and support large-volume digitization without increasing headcount.
A fully serverless Generative-AI IDP platform built on Amazon Bedrock, AWS Lambda, Step Functions, DynamoDB, S3, CloudFront, and API Gateway. The system automates page extraction, AI analysis, data structuring, validation, and API-based delivery.
The solution automates the entire document workflow, reduces processing from weeks to minutes, delivers higher accuracy via Bedrock/Claude, eliminates scaling constraints through serverless architecture, and enables the customer to onboard more clients with minimal manual review.
Highlighting some features, integrations or customizations:
The customer is a legal-tech company specializing in document digitization and legal process automation for SMBs, law firms, and public institutions across LATAM and North America.
Their platform transforms large volumes of legal case files into structured, searchable digital records while providing tools for case tracking and workflow automation, helping organizations modernize operations and improve efficiency in legal services.
We built a serverless IDP architecture using Step Functions, Lambda, Bedrock, DynamoDB, and S3/CloudFront, tested with real legal documents before launch.
The production deployment (May 2025) was developed by a joint team of cloud engineers and AI specialists. Challenges like low-quality handwriting and scaling inference were solved with Cross-Region Inference and parallel processing. Tooles contributed samples, validated outputs, and helped refine rules and templates.
Processing time was reduced from years to weeks.
The GenAI + serverless workflow enabled the customer to digitize and extract data from thousands of legal case files that would have taken 2.5 years manually, now completed in a few weeks.
The implementation highlighted the importance of iterative model refinement, especially when handling handwritten or low-quality documents, and validated the value of dynamic configurations and cross-region inference for scaling large IDP workloads. The solution has delivered long-term impact by reducing processing times from weeks to minutes, improving extraction accuracy, minimizing compliance risks, and enabling the customer to onboard new clients and scale operations without increasing headcount.
Looking forward, the customer plans to extend the platform to additional document types, automate more legal workflows, and incorporate advanced GenAI capabilities such as summarization and clause comparison while exploring the use of additional AWS services. The solution is also designed to be extensible, enabling future expansion into additional use cases and product lines as the customer’s needs evolve.
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