What challenges did Associa face before AI implementation?

Manual, time-consuming, and error-prone document classification across very large document volumes. Need to improve operational efficiency and reduce delays while maintaining high classification accuracy.

What was the impact of the AI solution?

Achieved 95% overall classification accuracy (443/465 documents) and reduced cost to 0.55 cents per document. Improved Unknown document type accuracy from 40% to 85%. Enabled scalable processing for high document volumes across branches.

Rank#580of 3,107

Source

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

−95%

costCost savings

+40%accuracy+85%accuracy

Strategic outcomes

Speed & agilityReduced document classification delaysNew product / capabilityBuilt AI document classification systemScale & capacityEnabled scalable high-volume processing

Catalog median for cost savings deployments: −45% across 345 reported metrics. Compare benchmarks →

Primary read

Use case focus

Showing 3 of 3

1Document classification
2Intelligent document processing
3Workflow automation

Manual, time-consuming, and error-prone document classification across very large document volumes.
Need to improve operational efficiency and reduce delays while maintaining high classification accuracy.

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.

Technologies

Amazon Bedrock Amazon Textract Amazon Nova Pro Amazon Nova Lite Amazon Nova Premier GenAI IDP Accelerator

Achieved 95% overall classification accuracy (443/465 documents) and reduced cost to 0.55 cents per document.
Improved Unknown document type accuracy from 40% to 85%.
Enabled scalable processing for high document volumes across branches.

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

AWS Generative AI Innovation Center

Sources & evidence1

Groundedness: 5/5Type: Blog PostPublished: Feb 5, 2026Publisher: AWSEvidence: VendorConfidence: Medium

Primary source

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