From Manual Testing to Confident Weekly Releases: How Faircado Scaled QA in 2 Weeks with QAI

Introduction

Faircado’s AI-powered browser extension and mobile app guide users from mainstream e-commerce platforms to second-hand alternatives—making circular shopping effortless for millions. By integrating over 60 million products across fashion, electronics, and books from 50+ partners—including eBay, Back Market, Grailed, Rebuy, and Vestiaire Collective—Faircado helps users make more sustainable choices without compromise.

After launching its mobile app in January 2025, Faircado saw rapid growth in usage and product releases. As shipping velocity increased, automated QA became critical to maintaining quality at scale without slowing development. With a compact and fast-moving team—CTO, Product Designer, and five Engineers—delivering high-quality features quickly is essential to keeping users engaged.

⚠️ The Challenge

As our user base and release frequency grew, quality assurance became a bottleneck. Like many early-stage teams, we relied on manual testing by the product team and co-founders. This approach had limits:

• No dedicated QA function or documentation

• Manual testing consuming 10–12 hours per week

• Coverage gaps across devices, OS versions, and core user flows

• Bugs occasionally surfacing via user feedback, delaying iteration

• Engineers pulled into testing instead of shipping features

We needed a scalable QA layer to boost confidence in every release—without adding process overhead or slowing our team down.

The QAI Solution

QAI enabled us to implement structured QA with minimal setup and no disruption. In just two weeks, their AI-powered agents transformed our testing workflow:

✅ No-code setup: QAI auto-generated test cases by exploring the app—no manual scripting or tagging needed.

✅ Real device coverage: Tests ran across real and emulated Android/iOS devices, covering combinations we couldn’t manually test.

✅ Agent-based execution: QAI agents mimicked real user behavior, making tests more resilient to UI changes and real-world flows.

✅ Visual reporting: Screen recordings and logs attached to each failure reduced debugging time and simplified issue resolution

Conclusion

QAI helped us build confidence in our weekly release process without slowing down development. It’s now a foundational layer in how we ensure quality at Faircado while staying lean and fast.