AI-Powered Applications
GlucoAlarm
Role: Solo architect and developer — product design, backend, integrations, and mobile app.
1. Challenge
Families managing a chronic health condition that requires continuous glucose monitoring need real-time alerts when readings cross dangerous thresholds — existing monitoring apps notify only the primary phone, with no redundancy if that alert is missed.
2. Business Requirements
- Sub-minute alert delivery with redundant channels (WhatsApp, SMS, and voice call escalation) so a critical alert is never silently missed.
- Tiered severity logic distinguishing routine, elevated, and emergency glucose events.
- AI-generated insight summaries that support awareness without ever issuing dosing or clinical recommendations.
- Multi-tenant account model with subscription billing and doctor/caregiver read-only access.
3. Proposed Architecture
An edge-deployed ingestion service pulls continuous monitor readings on a short polling interval, evaluates them against per-user threshold rules, and routes qualifying events through a tiered notification pipeline (WhatsApp first, SMS and automated voice calls as escalation fallbacks) backed by a serverless database for account, device, and alert-history state.
4. Implementation Approach
Shipped iteratively: core ingestion and threshold alerting first, then multi-channel escalation, then AI-generated trend summaries with explicit safety guardrails, then a native iOS app and multi-tenant billing to convert the tool into a subscription product.
5. Security Considerations
Treats all health data as sensitive by default: access is scoped per account, caregiver/doctor access is read-only, and the AI insight layer is constrained from producing medical dosing guidance under any prompt path.
6. Results
Operates as a live, real-world safety tool with redundant alert delivery, tiered severity, and production incident response experience (including hardening delivery pipelines after real-world load and quota issues). Converted from a personal tool into a subscription SaaS product.
7. Technologies Used
- Next.js
- TypeScript
- Cloudflare Workers
- D1
- Twilio
- WhatsApp Business API
- Anthropic Claude
- iOS (TestFlight)