Robinhood and Epsilon Transformations Using Amazon Bedrock for Generative AI
Use case typeAI platformUpdated Jun 13, 2026
Robinhood and Epsilon implemented generative AI solutions on AWS Amazon Bedrock platform. Robinhood scaled AI usage from 500 million to 5 billion tokens daily, cut AI costs by 80%, and halved development time while maintaining finance industry security and compliance. Epsilon automated complex marketing campaign workflows using Amazon Bedrock AgentCore, accelerating agent development from months to weeks and delivering personalized marketing at scale with reduced operational overhead.
- Organization
- Robinhood
- Industry
- Finance
- Location
- United States
- Published
- May 2026
Reported outcomes
Strategic outcomes
New product / capabilityScaled secure AI for financial innovationRisk & complianceMaintained finance-grade security and complianceNew product / capabilityAutomated personalized marketing workflowsSpeed & agilityAccelerated agent development cycle
Primary read
Use case focus
Showing 3 of 3
- 1Generative AI
- 2AI Agents
- 3Marketing Automation
- Robinhood faced challenges scaling AI usage securely and cost-effectively for financial innovation.
- Epsilon needed to automate and personalize marketing campaigns at scale while reducing operational overhead.
- Robinhood leveraged Amazon Bedrock's foundation models, security, and compliance features for AI at scale.
- Epsilon used Amazon Bedrock AgentCore to build and deploy intelligent AI agents securely and efficiently.
Technologies
- Robinhood democratized finance with AI at scale with enterprise-grade security and compliance.
- Epsilon enhanced marketing automation and personalization, accelerating agent development and reducing overhead.
Sources & evidence1
Groundedness: 4/5
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