Personalised GLP-1 Care with AI-Supported Patient Guidance
Connecting patient education, body composition insights, and clinician-led care planning through a Claude-powered platform.
Overview
A clinical weight care provider needed to give patients ongoing guidance while equipping clinicians to personalise care. 10Pearls designed and launched a HIPAA-aligned, Claude-powered platform that brings patient education, body composition insights, and clinician care planning into one connected experience, with dedicated AI capabilities for patients and clinicians.
with no paid marketing
iOS, Android & web
Challenge
Supporting more GLP-1 patients meant addressing three connected needs: creating personalised care plans without adding to clinicians’ workload, providing reliable education between appointments, and bringing body composition measurements into care decisions. Weight and BMI alone could not provide the same picture as tracking body fat, skeletal muscle and visceral fat over time.
The underlying AI models needed to work according to each audience’s needs. Patients needed clear, timely answers within educational boundaries. Clinicians needed more detailed support across patient information and care planning.
Solution
10Pearls brought patient education, body composition insights, and clinician care planning into one platform, giving the provider a connected foundation for AI-supported GLP-1 care. Our team delivered the product end to end, covering product management, mobile and backend engineering, AI, QA, and DevOps. The platform combines patient applications, a role-based clinician portal, body composition scanning through the Prism Labs SDK, and two distinct retrieval-augmented generation (RAG) pipelines powered by Claude through Amazon Bedrock.
Patient education with Claude Haiku 4.5. The patient-facing pipeline retrieves guidance that is grounded in the founding physician’s clinical methodology and keeps responses within an educational scope.
Clinical decision support with Claude Sonnet 4.5. The clinician-facing pipeline supports natural-language care plan generation using patient information and body composition trends across scans. The portal gives clinicians visibility into patient data and AI-assisted recommendations while preserving their authority over care decisions.
Both pipelines retrieve against a PostgreSQL knowledge store, with configurable guardrails defining their permitted scope. AI red teaming tests the assistants’ behaviour against unsafe and out-of-scope requests, supported by founding-physician sign-off. The platform accesses Claude through Amazon Bedrock and runs on HIPAA-aligned infrastructure.
The live platform gives the provider a unified way to support patients and equip clinicians with relevant information for care planning. By engineering distinct AI experiences for each audience within a shared product, 10Pearls established a foundation for expanding AI-supported services while maintaining clear boundaries between patient education and clinician-led care.
Results & Benefits
Phase 1 launched on August 10, 2026, across iOS, Android and the clinician web portal, recording more than 1,200 downloads without paid marketing. The dual-model architecture gives each audience its own AI experience that is matched to its role.
The delivered platform connects patient education, body composition tracking and clinician workflows within one product. Its patient assistant remains bounded to educational guidance, while the clinician assistant supports care plans subject to human review. A 20-person cross-functional team delivered the patient applications and clinician portal in parallel, with guardrails, AI red teaming and physician oversight forming part of the platform’s safety approach
Customer
Clinical weight care solution provider
SERVICES
- Product Engineering
- Mobile App Development
- Web App Development
- Generative AI Development
- AI Development
- IT Security
Tech stack
Powered by:
- Claude Sonnet 4.5
- Claude Haiku 4.5
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