How Faircado Scaled from Zero QA Process to Confident Weekly Releases in 2 Weeks

Introduction

Faircado is a Berlin-based startup on a mission to make second-hand shopping effortless. By aggregating listings from marketplaces like eBay, BackMarket, and Vestiaire Collective, their mobile apps (iOS & Android, Germany & UK) help users find sustainable alternatives to buying new.

With a lean tech team (CTO, Product Designer, and five Engineers), Faircado needed to ensure a smooth, bug-free experience to keep second-hand shoppers engaged and reduce churn.

⚠️ The Challenge

Without a dedicated QA function or automation in place, quality assurance at Faircado became increasingly difficult. Testing was handled manually and informally by co-founders, the product team, and the CTO without any written test cases or structured process. This led to several compounding issues:

• No formal QA process — test cases had never been documented or planned

• Fully manual testing — each release required 10–12 hours/week of hands-on testing

• Fragmented QA ownership — responsibilities split across product, engineering, and leadership

• Low test coverage — no scalable way to validate core flows across 4 mobile apps (DE/UK, iOS/Android)

• Missed bugs leading to churn — user feedback often revealed issues post-release, but debugging was slow due to a lack of visibility

• Uncertainty around release stability — especially on different OS versions and devices

• Engineer distraction: Critical engineering time was being burned on testing rather than feature development.

The QAI Solution

Faircado implemented QAI as their first-ever structured QA solution, turning an ad hoc process into an AI-powered system for test generation, execution, and reporting.
Here’s how QAI helped:

✅ No-code setup: QAI auto-generated end-to-end test cases directly from app exploration without any input from engineers, using specialised agents.

✅ Real device coverage: Tests were run on real and emulated Android/iOS devices, covering the combinations that Faircado couldn’t manually test.

✅ Test execution automation: Unlike traditional automation that relies on scripts or element IDs, QAI’s agents behave like real users. This makes tests more resilient to UI changes and real-world behavior.

✅ Visual reporting: Every failure is tied to a screen recording and log, so bugs are now easy to reproduce and fix.

With zero test cases in place before QAI, Faircado was able to go from manual chaos to 80%+ test coverage in just 2 weeks.

Results & Impact