Normalized claim
Model size reduction: 95% decrease
Velatura obtained a 95 percent smaller English-Arabic model that delivers comparable performance
Velatura Consent Manager+ explains healthcare consent in near real time using Amazon SageMaker AI
Use case typeConversational assistantsUpdated Jul 15, 2026
Velatura built Consent Manager+ to help patients understand complex healthcare consent forms with culturally and linguistically accurate explanations in near real time. The solution uses Falcon models on Amazon SageMaker AI with AWS services including Amazon S3, AWS Lambda, Amazon API Gateway, and related model access via Amazon SageMaker JumpStart and Amazon Bedrock Marketplace.
- Organization
- Velatura Public Benefit Corporation
- Industry
- Healthcare
- Location
- United States
- Published
- July 2026
Reported outcomes
−95%
model size reductionOther quantified impact
+100%pilot participation+75%Consent Champion Program enrollment
Strategic outcomes
Other strategic outcomeImproved patient understanding of consent formsMarket & geographic expansionExpanded support to additional languages and communitiesScale & capacityEnabled scaling across the United States and globally
Why do we believe this?Outcome claims, sources, and evidence checks
Normalized claim
Pilot participation: 100% increase
The initial pilot featured a diverse group, including Arabic and English speakers from multiple generations, and demonstrated immediate success with 100 percent participation
Normalized claim
Consent Champion Program enrollment: 75% increase
Seventy-five percent of Consent Manager+ users enrolled
Why do we believe this deployment?Customer identity, provider attribution, maturity, and source checks
- Customer
- Velatura Public Benefit Corporation
- Provider
- AWS
- Maturity
- Production
- Linked source
- AWS Customer Story
Deployed Falcon LLMs on Amazon SageMaker AI
Customer identity supportedSource describes one deploymentMaturity supported
Primary read
Use case focus
Showing 2 of 2
- 1Conversational assistants
- 2Multilingual communication
- Patients could not understand complex, multilingual healthcare consent forms.
- Velatura needed culturally and linguistically accurate explanations in near real time for diverse communities.
- Deployed Falcon LLMs on Amazon SageMaker AI.
- Built a mobile-first AskTeli AI assistant for natural-language consent explanations and expanded the solution to additional languages and community pilots.
- Achieved a 95% smaller English-Arabic model with comparable performance.
- The initial pilot achieved 100% participation, and 75% of Consent Champion Program users enrolled.
Architecture
Velatura built Consent Manager+ on AWS with Falcon models deployed on Amazon SageMaker AI. The solution uses Amazon S3 for document storage, AWS Lambda for processing logic, Amazon API Gateway for REST and WebSocket APIs, and model access through Amazon SageMaker JumpStart and Amazon Bedrock Marketplace. The application is a mobile-first AskTeli AI assistant delivering culturally and linguistically accurate explanations of healthcare consent forms in near real time.
Sources & evidence1
Evidence: Medium65/100Evidence strength
- Customer explicitly identified
- Deployment status explicitly supported
- Primary source available
- Quantified outcome available
- Technical implementation details available
Type: Customer StoryPublished: Jul 15, 2026Publisher: AWSEvidence: PrimaryConfidence: High
AI-generated summary. Verify important details with the linked sources before relying on this case.
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