PepMetrics

People running peptide protocols track a lot of data: dosages, schedules, bloodwork panels, sleep quality, HRV, body composition, and subjective well-being. Most of them are doing it across spreadsheets, notes apps, and memory. There's no single tool that connects protocol compliance with actual health outcomes.

Generic health apps don't understand peptide-specific workflows. They're built for step counting and calorie tracking, not for logging injection schedules, correlating bloodwork trends with protocol changes, or generating insights across multiple biomarkers over time.

PepMetrics was designed as a protocol-first health tracker. The data model starts with the protocol — what you're taking, how much, how often — and layers health metrics on top. This means the app can show you not just your numbers, but how those numbers correlate with what you're actually doing.

The dashboard surfaces the metrics that matter: daily compliance, fasting status, sleep and HRV trends, and upcoming injections. Bloodwork integration lets users track lab results over time and see how panels shift across protocol phases.

Progress tracking combines hard data (weight, body composition, lab values) with visual documentation (progress photos) so users can see the full picture, not just numbers on a chart.

The front end is built with Next.js 16 and a component stack designed for data-dense interfaces: shadcn/ui for layout primitives, Tremor for chart components, and Recharts for custom visualizations. The result is a dashboard that feels like a proper analytics tool, not a consumer health app.

Form handling uses React Hook Form with Zod validation, ensuring data integrity at the input layer. When you're logging health data that informs real decisions, every field needs to be validated and structured correctly from the start.

AI-powered insights analyze patterns across protocol adherence, health metrics, and bloodwork to surface correlations that would be difficult to spot manually.

PepMetrics fills a gap in the health tracking space by building specifically for the peptide and optimization community. It's not a general wellness app with a peptide feature bolted on — it's a purpose-built tool where the protocol is the foundation.

The application demonstrates that health tech doesn't have to be generic. When you build for a specific community and their specific workflow, the product is more useful, the data is more meaningful, and the insights are actually actionable.