Evidence: Low35/100

Automating contract intelligence with Doczy.ai on AWS

AArete’s Doczy.ai automates contract intelligence for healthcare organizations and other enterprises by converting unstructured contracts and legal documents into structured, queryable outputs on AWS.

Organization
AArete
Industry
Healthcare
Published
June 2026

Reported outcomes

−99%

timeTime & speed

−55%time−97%time

Strategic outcomes

New product / capabilityAutomated contract intelligence for healthcareSpeed & agilityStreamlined document processing and automationScale & capacityBuilt a centralized metadata repository
Why do we believe this?Outcome claims, sources, and evidence checks

Normalized claim

Time: 99% decrease

AWS Architecture BlogJun 2, 2026Blog postInferred claimLow evidence strength

The article reports about 99% accuracy versus 55% for rules-based systems, about 97% reduction in manual processing time, 2.5 million documents processed over 22 months, 137 million API calls to Amazon Bedrock, and about $330 million in cu...

Normalized claim

Time: 55% decrease

AWS Architecture BlogJun 2, 2026Blog postInferred claimLow evidence strength

The article reports about 99% accuracy versus 55% for rules-based systems, about 97% reduction in manual processing time, 2.5 million documents processed over 22 months, 137 million API calls to Amazon Bedrock, and about $330 million in cu...

Normalized claim

Time: 97% decrease

AWS Architecture BlogJun 2, 2026Blog postInferred claimLow evidence strength

The article reports about 99% accuracy versus 55% for rules-based systems, about 97% reduction in manual processing time, 2.5 million documents processed over 22 months, 137 million API calls to Amazon Bedrock, and about $330 million in cu...

Why do we believe this deployment?Customer identity, provider attribution, maturity, and source checks
Customer
AArete, Doczy.ai
Provider
AWS
Maturity
Unknown

No explicit deployment-stage evidence found.

Customer identity supportedSource describes one deploymentMaturity evidence evaluated

Primary read

Use case focus

Showing 3 of 4

  • 1Document Processing
  • 2Contract Analysis
  • 3Claims Automation
Healthcare organizations faced a major bottleneck manually reviewing and extracting data from thousands of unstructured contracts and legal documents, causing errors, delays, and slow translation of reimbursement terms into claims systems.
  • The solution uses Amazon Bedrock Agents and Amazon Bedrock Knowledge Bases, Amazon Textract, Amazon S3, AWS Lambda, Amazon ECS, Amazon Cognito, AWS Secrets Manager, and Amazon CloudWatch to process documents, chunk and cluster content, generate structured outputs, and feed downstream automation.
  • It integrates with contract management systems and downstream claims systems, creating a centralized metadata repository and supporting business process automation.
The article reports about 99% accuracy versus 55% for rules-based systems, about 97% reduction in manual processing time, 2.5 million documents processed over 22 months, 137 million API calls to Amazon Bedrock, and about $330 million in cumulative savings.
Architecture

Users upload documents through a secure Next.js frontend with Amazon Cognito authentication. Documents land in Amazon S3 and are processed with Amazon Textract. Doczy.ai applies smart chunking and dual clustering to preserve document structure and semantics, then uses Amazon Bedrock Agents and Amazon Bedrock Knowledge Bases to generate grounded structured outputs. The system orchestrates Amazon ECS, AWS Lambda, Amazon CloudWatch, and AWS Secrets Manager, and sends structured data to Snowflake and downstream contract management/claims systems via APIs.

Sources & evidence1
Evidence: Low35/100Evidence strength
  • Customer explicitly identified
  • Quantified outcome available
  • Technical implementation details available
Type: Blog PostPublished: Jun 2, 2026Publisher: AWSEvidence: VendorConfidence: Medium

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