MeetKai is an AI-based voice assistant app built to make life easier through conversation, personalization, and curation. The voice assistant helps users discover movies, TV shows, recipes, restaurants, and much more, all based on user preferences. MeetKai is also the first virtual assistant capable of understanding and remembering user question context due to its deep understanding of what the user is actually saying. With the company’s 1.0 version launch in May 2021, MeetKai is now available in 36 countries and in 13 languages.
We are going through an exciting growth journey in not just our user count but also the countries and languages we support. As a startup it is very hard for us to manage testing across 36 countries, 13 languages, with dozens of potential result types that could come as a reply from a virtual assistant. Sofy has been phenomenal in making sure that new features and regions we add don’t break our old ones. Regression testing done with Sofy has been a game changer in our productivity and release velocity and most importantly our confidence we have when we submit each build. Sofy has been extremely responsive and helpful throughout our journey in migrating to their platform, but even without their help their tooling is streamlined enough to get going very quickly.
Co-Founder & CEO, MeetKai
Consumer apps, Voice AI, Concierge
SAVING TIME SINCE
FEATURES MOST USED
Device Lab, No-code automation
Tens of thousands of users across the globe depend on MeetKai as their phone’s virtual assistant. It was critical that the company’s app provided a fast and accurate response, not to mention a kickass user experience. Since the MeetKai crew was quite lean and growing fast, it faced challenges associated with the quality assurance aspect of the DevOps cycle:
Being a lean team, MeetKai needed cost-effective and efficient solutions that scaled well. Sofy assisted the team with:
Sofy helped MeetKai keep up with the speed of their engineering releases by improving the speed of quality assurance. The team began with device lab and from there took less than a week to automate app scenarios using no-code automation. Once test cases were set up, the company’s engineer team simply triggered testing of new builds from their release cycle.
Test Use Cases
Time to Automate Once
Total Time Saved