case://study-004
AI / ML
Project 004

Viral OS

Viral OS is the operations dashboard for a B2C app studio. It ingests App Store Connect (sales + metadata), RevenueCat (101 webhook event types), TikTok (via a Playwright scraper running on GitHub Actions, not the paid API), and manual ad spend; computes metrics that aren't in any individual tool — predicted LTV (geometric with realized-churn fallback), LTV/CAC, cohort retention, app-health score (0–100), lifecycle stage; and fires Slack/Discord/email alerts the same day a paywall regression or refund spike appears.

14
API Routes
19
Dashboard Pages
10
DB Migrations
AI / ML
Category
The Problem

What Wasn't Working

Studios shipping a portfolio of apps lose hours every week stitching together RevenueCat, App Store Connect, TikTok analytics, and ad spend across separate dashboards. By the time a paywall regression shows up in a monthly review, the damage is done.

The Solution

How I Fixed It

One Supabase-backed dashboard pulls every data source into a unified schema. Hand-rolled detectors (EWMA + 2σ on revenue + refunds + MRR drops + rating drops + rejected builds) catch anomalies same-day. Gemini 3 Pro is wired into every surface via tool-use, not stuffed context — the AI queries the live DB instead of getting fed it.

Stack

Technologies Used

Next.js 16
Supabase
Gemini 3 Pro
RevenueCat
App Store Connect
Playwright
Sentry
Results

Key Outcomes

Single dashboard replaces RevenueCat + ASC + TikTok + spreadsheet tabs
Same-day anomaly alerts on Slack / Discord / email
Predicted LTV + cohort retention + app-health score, all computed in-app
Zero paid analytics SDK — every metric derived from raw events

Want something like this?

Let's build it. I ship fast and I ship clean.