RAZER AI GAME DEV TOOLS
RAZER QA CO-AI
Automate and streamline QA with an AI companion
Direct Bug Sync
to JIRA
Performance Regression
tracking
AI-Driven Gameplay
Bug Analysis
Available via WYVRN SDK
Boost your QA efficiency with Razer QA Co-AI (also known as QA Companion) — a cloud-based tool that automates bug detection and performance tracking during playtests. It takes care of the repetitive work for QA testers, automatically logging crashes and performance issues in real time, and generating clear reports with screenshots, video clips, and event data.
Compatible with Unreal Engine, Unity and custom C++ engines.
Core features
Record gameplay issues in one click
Razer QA Co-AI optimizes QA testing for games by making bug reporting fast, visual, and reliable.
With a single click, QA testers can capture a 20-second gameplay video leading up to an issue,
giving developers immediate visual context to understand, reproduce, and fix bugs more efficiently.
- Instant video capture: One-click bug recording of the moments before an issue occurs during gameplay.
- Annotated screenshots: Visual notes added directly to captured images to highlight problem areas for developers.
- Hotkeys: Ctrl + B captures a screenshot, and Ctrl + Shift + B records the last 20 seconds of gameplay, allowing precise capture of bugs.
- Optimized format: Videos are encoded in .MP4 (1080p, 3 Mbit/s) for high-quality playback without affecting in-game performance.
- Secure cloud storage: Captures are automatically uploaded, stored for 24 hours, and then securely deleted.
- Faster debugging workflow: Real-time video context improves QA efficiency, reduces tester–developer handoff time, and accelerates issue reproduction.
Automate performance bug tracking
Performance testing is a crucial step in game QA, and Razer QA Co-AI helps automate it from end to end.
Designed for QA teams and developers, it continuously monitors gameplay to detect performance drops,
track key metrics, and flag potential bottlenecks before they impact players.
- Real-time metric tracking: Monitors CPU usage, frame rate (FPS), RAM consumption, and GPU load during playtests.
- Customizable thresholds: Detection sensitivity configurable to align with specific project performance standards.
- Hardware-aware reporting: Logs include a full hardware configuration snapshot for accurate context.
- Automatic video capture: Records a 20-second gameplay clip for each detected issue, providing visual evidence for faster debugging.
- Hardware flexibility: Works seamlessly across high-end and low-spec systems, ensuring consistent QA performance testing across builds.
Streamline bug reporting to Jira
Efficient bug reporting is essential for smooth QA testing workflows.
Razer QA Co-AI streamlines bug reporting with built-in Jira integration,
enabling QA testers to capture, describe, and send issues directly to developers.
- Structured reporting: Testers can add a bug description, expected result, actual result, and reproduction steps for clear issue documentation.
- One-click Jira export: Automatically generate and send a Jira ticket without leaving the QA Companion interface.
- Seamless integration: Connects directly with existing development pipelines, reducing friction between QA and engineering teams.
- Improved collaboration: Ensures each bug report includes complete context, enabling faster diagnosis and resolution.
Calibrate your QA workflow with third-party data
To deliver smarter, faster, and more reliable QA workflows, Razer QA Co-AI integrates
third-party data sources that enhance bug detection, classification, and resolution.
- Game Engine Logs Ingestion: Seamlessly ingest runtime logs from leading engines like Unity, Unreal Engine, and custom C++ frameworks. This enables deeper context around crashes, performance anomalies, and gameplay-triggered issues, empowering your Razer QA Co-AI to pinpoint root causes with greater accuracy.
- Jira Project Data Ingestion for Bug Deduplication: Our system leverages AI language analysis to scrape and analyze Jira tickets, intelligently identifying duplicate bug reports across projects. This reduces noise, streamlines triage, and improves prioritization by surfacing recurring issues and linking related reports with contextual awareness.
AI-enhanced gameplay debugging
Razer QA Co-AI brings AI-powered debugging to game QA testing,
automatically detecting design-related bugs by analyzing in-game events
for logical inconsistencies and broken gameplay flows.
- AI-driven detection: Uses fine-tuned machine learning models to identify unexpected behaviors, missing triggers, and sequence breaks in real time.
- WYVRN SDK integration: Seamlessly connects with the WYVRN SDK, leveraging embedded game design inputs for context-aware analysis.
- Intelligent event tracking: Embeds automated tracking directly into gameplay to surface subtle design flaws early in testing.
- Reduced manual debugging: Cuts down repetitive investigation work by highlighting likely root causes automatically.
- Genre support: Currently supports first-person and third-person shooters, with broader genre coverage in development.
How it works with game and QA studios
ONBOARDING TUTORIAL
This tutorial guides you through the initial setup of Razer QA Co-AI, including installing the Razer AI Service, configuring your first project, and connecting to Jira for seamless bug tracking. You’ll learn how to define performance thresholds, launch QA sessions, and capture gameplay issues with video-backed reports, all designed to help streamline your QA workflow from the very first session.
START TESTING WITH QA CO-AI
Experience a faster, smarter way to test and ship your games. Razer QA Co-AI combines automation, AI-driven insights, and seamless integration to help teams catch issues earlier, improve performance, and deliver more stable builds with less effort.