Catchy Labs
CatchyApp — QA Hiring & Performance

Hire and grow QA engineers on data, not gut feeling.

CatchyApp evaluates QA engineers — candidates and current team members — through real test scenarios across web, mobile and API clients, with automated scoring and multi-level review.

Book a demoOpen CatchyApp

Run interviews and performance reviews with the same tool. Hiring junior QA? See our 8-week bootcamp →

How it works

Real test scenarios. Automatically scored.

Same workflow whether you’re interviewing a candidate or evaluating a member of your team.

  1. 01

    Define a challenge

    Pick a client app, configure bugs by type and severity, set a time box.

  2. 02

    Run a session

    Candidates or team members open the challenge, find bugs, document test cases, and submit reports.

  3. 03

    Score & review

    CatchyApp scores the session automatically; managers and directors review with full audit trail.

Capabilities

Everything you need to evaluate QA engineers.

Challenge & Session Management

Create timed test scenarios using purpose-built client apps with intentional bugs. Assign challenges to candidates or current team members.

Multi-Client Testing

iOS, Android, web and API clients in one platform. QA engineers practice on the same client mix they’ll see on the job.

Bug Detection & Taxonomy

Configurable bug types (incorrect response, timeout, sequential, client-specific) with severity levels and trigger conditions.

Automated Performance Scoring

Scores based on bugs found, efficiency, test-case quality, and reporting thoroughness. Manual override available for managers.

Multi-Level Review

Manager evaluations with director override. Built-in fairness for hiring and performance decisions that need to stand up to scrutiny.

Personnel & Goals

Track QA engineers over time. Manage cohorts, assign challenges, and follow OKR-style performance goals across the team.

CatchyAI — built into CatchyApp

AI-assisted evaluation, not AI-replaced judgment.

CatchyAI reviews each session’s bug reports and test cases, surfaces patterns across candidates, and gives managers a starting point for conversation. Final calls stay with humans — every suggestion is explainable and overridable.

Session #2401CatchyAI · summary

Strong on edge-case discovery (timeout + sequential bugs found in 14 min). Weaker on test-case documentation — reports lack reproduction steps for 3 of 7 issues.

  • Bug detection accuracy: 93%
  • Report thoroughness: 61%
  • Suggested follow-up: pair on regression-coverage exercises

CatchyApp

Ready to make QA hiring defensible?

Book a 30-minute demo and we’ll walk you through CatchyApp on a real challenge — interview or performance flow, your call.

Book a demoOpen CatchyApp