Financial care platform serving 800,000+ families streamlines GenAI on AWS
Industries
Financial services,
Employee wellbeing
Tech & TOOLS
Amazon Bedrock, AWS
Teams & Services
AI & Agentic, AWS Engineering
milestones
Streamlined AI operations, enhanced security, easier data integration, AWS-native GenAI foundation
Industry
Financial services,
Employee wellbeing
Tech & TOOLS
Amazon Bedrock, AWS
Teams & Services
AI & Agentic, AWS Engineering
milestones
Streamlined AI operations, enhanced security, easier data integration, AWS-native GenAI foundation
The company evaluated Amazon Bedrock as a more unified AI foundation to streamline operations, strengthen security, and support future innovation.
The situation
A leading financial care platform helps employers support the financial health of their employees and families. Its technology combines personalized financial solutions, technology-powered assistance, and human support to help people navigate everything from immediate financial challenges to long-term financial goals.
As the company continued to expand its AI capabilities and explore new generative AI applications, it needed an infrastructure that could support innovation at scale while simplifying its technology environment.
The team was using Databricks and OpenAI models for its AI workloads and wanted to evaluate the benefits of transitioning to a more AWS-native architecture. It partnered with Loka to assess how Amazon Bedrock could support its generative AI strategy while consolidating its infrastructure under AWS.
The challenge
The organization wanted to increase its generative AI capabilities without increasing operational complexity across multiple platforms and services.
Its existing environment relied on Databricks and OpenAI models, creating an opportunity to simplify operations by bringing more of its AI infrastructure into AWS. The company also needed to evaluate how a new architecture could support stronger security and easier integration with additional AWS data services.
Before making a broader migration decision, the team needed a practical way to evaluate Amazon Bedrock and understand how the platform could support its current and future AI initiatives.
The solution
Loka conducted a fully funded OpenAI Migration Assessment to evaluate the company's existing AI environment and explore an AWS-native alternative.
As part of the assessment, Loka developed a pilot for production using Amazon Bedrock to demonstrate how it could migrate its generative AI workloads from OpenAI while consolidating more of its infrastructure within AWS.
The proof of concept gave them a practical foundation for evaluating Amazon Bedrock and the benefits of a more unified AWS architecture. The assessment demonstrated opportunities to streamline operations, strengthen security, and simplify integration with additional data services.
What we delivered
OpenAI migration assessment
1 strategic assessment: Loka evaluated the existing AI environment and identified opportunities to transition generative AI workloads to AWS.
Amazon Bedrock proof of concept
1 working prototype: Loka developed a pilot of production using Amazon Bedrock to demonstrate an AWS-native approach to generative AI.
Streamlined AI infrastructure
1 consolidated direction: The assessment showed how moving from OpenAI models to Amazon Bedrock could simplify the technology environment.
Enhanced security
Improved control: Consolidating AI infrastructure under AWS created opportunities to strengthen security and simplify infrastructure management.
Foundation for innovation
Expanded integration: An AWS-native architecture made it easier to connect generative AI capabilities with additional AWS data services as strategy evolves.
The results
The company validated a path to AWS-native GenAI with Amazon Bedrock, simplifying operations, enhancing security, and creating a foundation for future AI innovation.
Streamlined operations: Reduced complexity by evaluating a more consolidated, AWS-native AI infrastructure.
Amazon Bedrock pilot of production: Demonstrated how generative AI workloads could transition from OpenAI to AWS.
Enhanced security: Created a more unified foundation for managing AI infrastructure within AWS.
Improved integration: Made it easier to connect AI capabilities with additional AWS data services.
Foundation for innovation: Established a clearer path for scaling future generative AI initiatives.
