back_office_ops · realestate · workflow
Associa transforms document classification with GenAI IDP Accelerator and Amazon Bedrock achieving 95% accuracy
Associa manages approximately 48 million documents across 26 TB of data but lacked automated classification, forcing employees to spend countless hours manually categorizing incoming documents—a time-consuming, error-prone process creating operational bottlenecks and reduced productivity.
How it works
Common implementation structure
How this type of workflow is generally built, generalized across documented cases — not tied to any one vendor's stack. Click any stage to read what happens there. Specific products that implement these stages appear in “Tools commonly seen” below.
Stage 1 · Incoming document received
Employees receive incoming documents that require categorization and organization every day.
Tools used
Amazon BedrockAmazon TextractGenAI IDP AcceleratorAmazon Nova ProAWS CloudFormationAnthropic Claude Sonnet 4
Outcome
Associa's generative AI-powered classification system achieves 95% overall accuracy at 0.55 cents per document using Amazon Nova Pro on Amazon Bedrock, with the CIO foreseeing significant reduction of manual effort and reporting substantial cost savings.
Results
Volume95%
Cost replaced0.55 cents
Grounding & classification
Source type: technical build writeup
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document aidocument classificationidpocrcontractpolicy documentbuilder submittedhuman review describedmetric backednamed customerproduction runtime claimedtools describedvendor confirmedworkflow describedreal estateaccuracy improvementautomation ratecost reductionemployee productivitytechnical build writeupback office opsdata entry opsdocument to recordextract classify route