iOS app applying ML and computer vision to fashion shopping.
Acquired by a major tech company ~1 year after launch.

The Challenge

  • Screenshop came to us looking for a fast path to a first release of their fashion / AI app.
  • They had already built something cheap to test the technology and raise money, but they’d reached the limit of their first team’s capabilities.
  • Now they needed a serious offering in the app store by Black Friday, which was five weeks away.
  • Ultimately the goal was for the product and company to be acquired.

The Work

  • We optimized the initial build for speed, making trade-offs where appropriate.
  • We implemented client side computer vision and machine learning to improve response times and preserve user privacy.
  • We ran extensive A/B tests within the app to determine what was most effective.
  • We established an aggressive release schedule and implemented sophisticated analytics, to understand user behavior.
  • We iterated constantly, often releasing multiple times per week.

The Results

  • Tap Clinic built and launched the first version of the app in five weeks, on time.
  • We were featured by the App Store in the first week.
  • We grew to 250,000 users organically in the first four months.
  • Screenshop was acquired by Snap Inc just over a year after launch.
"Tap Clinic built our app from scratch after we were burned by some bad early technical decisions, and they've been a reliable partner with us for over a year now.

They manage every technical aspect of our app, which now has hundreds of thousands of users: the engineering, release processes, A/B testing, analytics, and the QA.

Having such experienced people just helps everyone here sleep at night, and lets us focus on our core technology and business. I'd absolutely recommend working with them."
Timothy Hyde headshot

Tim Hyde

VP Engineering, Screenshop

(acquired by Snap Inc)