venture
TUVA — from Swift prototype to 10,000 users in three weeks
In one line: I founded TUVA in Swift and Java; it reached 10,000 users in three weeks, with Mixpanel and Google Analytics shaping product decisions from launch.
Context
Neighbourhood safety needed a simple reporting loop on mobile — maps, zones, notifications — not a corporate IT project.
Why it was worth building
The question was whether a founder-led native app could earn trust and daily use quickly. Without behavioural data from day one, growth would have been guesswork.
What I built
- Native iOS and Android clients with real-time reporting and geographic zones.
- Backend integrations — Parse, MongoDB, Twilio, Heroku-era hosting.
- Product analytics — Mixpanel and GA for onboarding, activation, and retention.
How it was adopted
Users joined through local rollout; analytics drove iteration on flows that blocked activation.
Effect
10,000 users within three weeks of traction-focused launch; first experience owning an entire product surface.
Where AI fits now
Founder metrics and experiment discipline from TUVA carry forward: measure adoption before scaling automation. Agents and AI features still need the same question — what decision changes if this ships?
Want to compare notes?
I am always interested in thoughtful conversations about the decisions, trade-offs, and systems behind this work.
Get in touch