Intelligent Document Processing with GenAI

Basis’ Intelligent Document Processing (IDP) with GenAI streamlines the extraction, classification, and enrichment of unstructured and semi-structured documents using AWS-native services. With tailored support across Financial Services, Life Sciences, and SMB markets, our service transforms manual workflows into automated, insight-rich pipelines through the power of Generative AI, OCR, NLP, and embedding techniques. We leverage tools such as Amazon Textract, Amazon Bedrock, Amazon Comprehend, and Amazon Kendra to deliver scalable, cost-efficient solutions that reduce processing times and drive measurable outcomes.

Outline of Approach: (phases and timelines may vary based on use case and data)

Discovery & Use Case Validation (1-2 weeks): We begin by aligning document processing goals with business objectives across departments such as finance, operations, or compliance. This phase is a complimentary step provided by Basis to assess and mobilize properly upon discovery.

• Conduct discovery workshops to identify target document types and key workflows.
• Assess current manual processes and automation opportunities.
• Evaluate model types (e.g., OCR, embeddings, summarization) aligned with AWS services.
• Define project KPIs and risk considerations. *** Determine qualifications for partner & AWS funding opportunities.**
• Deliver a discovery report with a validated use case and architecture plan.

Data Assessment & Architecture Design (1 week): Our Senior Engineering Managers assess existing document formats, quality, and storage strategies to build a scalable architecture.

• Audit existing structured/unstructured document repositories (PDFs, scanned forms, etc.).
• Plan secure ingestion using Amazon S3 and AWS Lambda.
• Select the optimal toolchain, including Amazon Textract, Bedrock models, Comprehend, and Kendra.
• Design a fault-tolerant, serverless architecture aligned with your compliance requirements with AWS SA architecture framework reviews along the way.
• Document & record usage via the AWS Pricing Calculator to assess infrastructure costs & funding opportunities for the PoC.

PoC Development & Automation Build (4-8 weeks): We develop a working Proof of Concept that showcases intelligent parsing, classification, and enriched document insights.

• Set up the extraction and processing pipeline (OCR, NLP, LLM).
• Fine-tune prompts or embed custom documents into Bedrock-compatible RAG pipelines.
• Leverage Bedrock for summarization or contextual responses.
• Apply Comprehend for entity recognition, sentiment, and compliance tagging.
• Build outputs into dashboards, searchable formats, or downstream systems.

Testing, Tuning & Knowledge Transfer (2-4 weeks): We validate output quality and prepare your team to take ownership post-deployment.

• Conduct QA and document-level validation testing.
• Tune prompts or parsing rules based on UAT & business feedback.
• Train internal teams to manage and extend the pipeline.
• Provide documentation, deployment guides, and an implementation roadmap.

From Assessment & Design to PoC Deployment & Tuning, Basis helps organizations eliminate paper-based bottlenecks, improve data accuracy, and unlock business-critical insights, whether processing invoices, insurance forms, clinical trial documents, or internal reports.

Production Scaling (Optional Next Phase): This GenAI PoC engagement is designed to lead directly into a production rollout. Upon PoC approval, the client and Basis can extend the working relationship with scalable automation, workflow orchestration, and full document lifecycle integration across business systems. This may also include development of a custom platform that manages entire lifecycles of parceled documents, data, etc...