Normalized claim
Cost: 95% decrease
Achieved 95% overall classification accuracy (443/465 documents) and reduced cost to 0.55 cents per document.
How Associa transforms document classification with the GenAI IDP Accelerator and Amazon Bedrock
Use case typeIntelligent document processingUpdated Jun 13, 2026
Associa, North America’s largest community management company, oversees approximately 7.5 million homeowners with 15,000 employees across more than 300 branch offices. The company manages approximately 48 million documents across 26 TB of data, but its existing document management system lacked efficient automated classification capabilities, creating manual bottlenecks and operational delays. Associa collaborated with the AWS Generative AI Innovation Center to build a generative AI-powered document classification system integrated into existing workflows using the GenAI IDP Accelerator on AWS.
- Organization
- Associa
- Industry
- Real Estate
- Location
- United States
- Published
- February 2026
Reported outcomes
Accuracy: 40% to 85%
Quality & accuracy
Catalog median for quality & accuracy deployments: +40% across 55 reported metrics. Compare benchmarks →
Why do we believe this?Outcome claims, sources, and evidence checks
Normalized claim
Accuracy: 40-85% increase
Improved Unknown document type accuracy from 40% to 85%.
Why do we believe this deployment?Customer identity, provider attribution, maturity, and source checks
- Customer
- Associa
- Provider
- AWS
- Maturity
- Production
- Linked source
- AWS Machine Learning Blog
The company manages approximately 48 million documents across 26 TB of data, but its existing document management system lacked efficient automated classification capabilities, creating manual bottlenecks and operational delays
Customer identity supportedSource describes one deploymentMaturity supported
Primary read
Use case focus
Showing 3 of 3
- 1Document classification
- 2Intelligent document processing
- 3Workflow automation
- Built a document classification system with the GenAI IDP Accelerator on AWS.
- Used Amazon Textract OCR and Amazon Bedrock multimodal classification with Amazon Nova Pro / Nova Lite / Nova Premier.
- Evaluated full PDF vs first-page-only input and OCR+image vs image-only prompting, then selected the first-page-only OCR+image approach with Amazon Nova Pro for the best accuracy-cost tradeoff.
Improved Unknown document type accuracy from 40% to 85%.
Architecture
The solution uses the AWS GenAI IDP Accelerator in Pattern 2 with Amazon Textract OCR plus Amazon Bedrock multimodal classification. Associa evaluated full PDF versus first-page-only inputs, OCR+image versus image-only prompting, and several Amazon Nova models to select the optimal configuration.
Implementation partners1
Sources & evidence1
Evidence: Medium50/100Evidence strength
- Customer explicitly identified
- Deployment status explicitly supported
- Quantified outcome available
- Technical implementation details available
Type: Blog PostPublished: Feb 5, 2026Publisher: AWSEvidence: VendorConfidence: Medium
AI-generated summary. Verify important details with the linked sources before relying on this case.
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