Theranica

Discover how Theranica, a digital therapeutics company, partnered with AllCloud to optimize its MLOps and scale AI capabilities on AWS SageMaker for its Nerivio migraine care app.

• Seamless Production Deployment: Learn how Theranica successfully introduced real-time and batch ML workflows into an active production environment without disrupting current app users.
• Optimized MLOps on AWS: Discover how utilizing Amazon SageMaker streamlined model management, tracking, and automation across the entire ML lifecycle.
• Internal Capability Building: Understand how AllCloud’s hands-on guidance empowered Theranica’s in-house data team with the expertise to independently develop future AI initiatives.
• Enhanced User Engagement: See how deploying advanced AI features enabled patients to better understand migraine patterns and improved adherence to clinical instructions.

Theranica  is a growth-stage neuromodulation therapeutics company redefining migraine care and other neurological disorders through its proprietary Remote Electrical Neuromodulation (REN) technology. Grounded in the science of Conditioned Pain Modulation (CPM), REN leverages the body’s natural pain-inhibitory pathways to provide clinically validated, drug-free treatment. Theranica’s flagship product, Nerivio®, is an FDA-cleared wearable for the acute and preventive treatment of migraine. Through the Nerivio app, patients gain access to advanced digital health tools, including AI-powered features and software enhancements that help identify migraine patterns, track treatment effectiveness, improve adherence to care plans, and support more informed disease management.

The company was looking to develop and scale the AI capabilities of its customer-facing app, Nerivio. Part of the challenge was to make their machine learning (ML) processes easier to manage, track, and automate – both to enhance app performance and optimize operational capabilities. As the app was already being used by customers, it was important that the implementation and roll out of the new AI features be seamless. In addition, deploying AI capabilities into its AWS-based production environment was a new undertaking for the company.

Theranica was committed to delivering a production-ready, scalable solution, and they turned to AllCloud, their AWS partner, for MLOps guidance and assistance. Theranica’s data team was responsible for the ML implementation – from data investigation through production deployment, including ongoing monitoring and production support. They worked closely with AllCloud’s AI team for targeted guidance throughout the implementation, enabling a smooth rollout.

AllCloud helped Theranica optimize their ML operations and processes, which ran across two processing workflows: batch and real-time inference. They provided strategic guidance for Theranica to utilize SageMaker, AWS’s fully managed cloud platform.

AllCloud provided hands-on support to Theranica for the successful development and deployment of the new AI feature, delivered on time. The feature not only enhanced the app’s capabilities but also led to increased user engagement. Furthermore, the company now has the internal knowledge and capabilities to implement additional AI-based features, both for product enhancement and for the optimization of internal operations and capabilities.

Theranica continues to monitor the ML feature and make adjustments as needed. Building on the success of the engagement with AllCloud – which demonstrated the value of AI capabilities within the app and helped build internal expertise -the company is now well-positioned to develop and deploy additional custom, scalable AI solutions on AWS.