The brief: a tracker people could actually trust

Appxcel needed a first product that proved the studio's whole approach — one app, built carefully, shipped honestly. A period and ovulation tracker was the right test case: it's used daily, the data behind it is about as personal as data gets, and most of the existing options in this category are cluttered with ads or built around monetizing exactly the data a user least wants shared. Monthlys had to do better on both fronts — genuinely useful predictions, and a private, ad-free experience.

Building predictions that adapt, instead of assuming a 28-day cycle

The easy version of a cycle tracker hardcodes a 28-day average and calls it done. That's wrong for a large share of real users, and it gets more wrong the longer someone relies on it. Monthlys instead logs a user's actual cycle history and recalculates period and fertile/ovulation windows from that history, so predictions get more accurate the longer the app is used rather than staying pinned to a textbook number.

How Monthlys turns logged data into a prediction adaptive, not fixed
01LogUser logs period start/end and symptoms as they happen.
02LearnApp recalculates cycle length and variability from real history.
03PredictPeriod and ovulation windows update to match the user's own pattern.
04AssistThe AI assistant answers questions grounded in that same logged data.

An AI assistant that only knows what the user told it

Rather than a generic chatbot bolted on for marketing, Monthlys's AI assistant is scoped to a user's own logged history — cycle length, symptoms, patterns over time — so its answers are about that person's own data, not a canned FAQ. It's built to help someone understand their own patterns, not to replace medical advice.

Shipping on Android as a Capacitor app, not a thin wrapper

Monthlys ships as a real Capacitor Android app (package com.appxcel.monthlys) with its web assets bundled into the APK at build time, which is what makes an honest in-app "update available" check possible — the app can read its own installed version and compare it against the latest release, something a plain TWA wrapping a live URL can't do. The release APK signs inline through Gradle's own signing config, and the same web app installs on iOS as a home-screen PWA.

A real production fix, not just a demo: an early version of the in-app update banner opened the raw APK file directly in a background browser tab — a download that could stall silently near completion. It was fixed to send users to Monthlys's own Appxcel Store page instead, so the download only ever starts from a real, foreground tap on an actual Download button.

Distribution: the Appxcel Store, with a scan users can verify

Monthlys is distributed through the Appxcel Store rather than Google Play — the Android APK is scanned against VirusTotal before it's ever listed, giving users a verifiable clean-scan result up front instead of asking them to trust an unfamiliar download blind.

2-in-1Period and ovulation tracking in one app
AIAssistant grounded in the user's own logged data
Android + iOSCapacitor app plus an installable PWA

The result

Monthlys shipped as a working, adaptive cycle tracker with real update infrastructure behind it — not a prototype. It's proof that Appxcel's approach holds up end to end: product design, a working AI feature grounded in real user data, a signed and scanned Android release, and a distribution channel Appxcel controls itself. Read more about the company behind it in the Appxcel case study or the Monthlys article.