Our client is a global medical company that creates innovative solutions that transform patients’ lives. Its flagship system provides therapy for a diverse range of neurological conditions.
The system's devices gather a huge volume of data on neurological activity and responses to stimulation. That data is collected and visualized in data platforms, enabling patients and clinicians to track conditions accurately and adapt treatment plans accordingly.
But as this company began to grow rapidly, it noticed its data platforms couldn’t scale as quickly as needed. SLAs started to slip, reporting times grew, and clinician and patient experiences were beginning to be negatively impacted.
To help tackle those challenges and prepare its data platforms for many more years of growth, it reached out to Thoughtworks.
The challenge: Migrating hundreds of thousands of lines of code to the cloud
As an innovative healthtech startup, our client only had a small data team. However, due to the complexity of solutions and underlying data analysis capabilities, the team had built a legacy system comprised of over 500,000 lines of code. To move this system to a more scalable and future-ready foundation in the cloud, each of those lines would need to be migrated efficiently and consistently.
To support the organization’s goal of building a highly scalable and capable foundation for the future growth of its business and data landscape, Thoughtworks recommended migrating to a new cloud-native data platform on Amazon Web Services (AWS).
Thoughtworks took a cloud-first approach to creating the new data platform foundation. We retrofitted applications to leverage event-driven AWS-native services, and used AWS Lambda and Fargate to enable serverless computing. We also migrated data processing to Databricks to support rapid and continuous data streaming.
By working in close partnership with AWS and Databricks, we’ve delivered a robust data platform solution that can be trusted and depended on as it grows. By combining Thoughtworks’ deep technical expertise with our partners’ leading capabilities and technology, we created something that none of us could have delivered alone.
Our approach: Streamlining the AWS migration journey
With so much legacy code in the system, Thoughtworks used code LLMs to accelerate the migration and implementation process. We leveraged code LLMs and AI-assisted development as a migration copilot to accelerate implementation and streamline complex code refactoring, freeing our experts to focus on helping teams adopt and embed cloud-native processes tailored to the client’s new infrastructure.
Thoughtworks’ AI capabilities, alongside our deep technical expertise, enabled the successful delivery of a complex solution within a tight timeline. Throughout the process, we continuously optimized our approach to ensure the client achieved the ideal balance of performance, cost and scalability.
The outcome: Faster reporting, improved scalability, and optimized costs
Thanks to the performance and efficiency gains enabled by the AWS cloud, the time required to generate critical clinical reports has reduced from hours at peak times to under 10 minutes.
Crucially, thanks to expanded scalability, as the organization grows and more patients’ lives are transformed with its devices, it can maintain that performance level — so growth never comes at the cost of patient or clinician experiences.
The organization’s transition to cloud-native, serverless and event-driven processing has also significantly reduced operational overheads, enabling them to focus resources on what really matters: improving patient outcomes.
With a scalable, cloud-based foundation in place, we can transform more patients’ lives with confidence. We can evolve faster, deliver more consistent performance, provide reports in minutes, and focus more of our time and attention on patient-centric innovation.
