Quality assurance · Production

Cathay achieves 40% tech debt improvement and 63% MTTR reduction with GitHub Copilot

The problem

Cathay's developers faced an outdated, fragmented toolchain that eroded the developer experience and slowed delivery, while late-breaking security vulnerabilities created serious risk to business functions and made it difficult to ship secure, compliant solutions.

Workflow diagram · grounded in source
1
Developer coding request in IDE
trigger
“Developers now receive real-time suggestions in the IDE to speed up everyday tasks”
2
Copilot code completion
ai_action
“Cathay's developers embraced GitHub Copilot for code completion”
3
Agent mode multi-step execution
ai_action
“agent mode handles more complex changes, indexing hundreds of files and executing multi-step prompts across the codebase”
4
Embedded security scanning
validation
“With GitHub Advanced Security, they embedded security checks directly into developer workflows—enabling faster fixes, earlier detection, and fewer handoffs between teams”
5
Copilot Autofix remediation
ai_action
“Copilot Autofix has added another layer of efficiency by detecting vulnerabilities and suggesting secure code changes in real time, without disrupting developer flow”
6
Developers ship secure code
output
“Developers are now able to identify and remediate vulnerabilities as they work, which virtually eliminates the delays that had been caused by late-stage fixes”
Reported outcome

Cathay achieved a 40% year-over-year improvement in tech debt fixes and a 63% decrease in Mean Time to Remediate security vulnerabilities, while rolling out GitHub Copilot to more than 1,000 developers in one week, accepting over four million lines of code, and raising developer satisfaction and NPS scores to 4.4/5.

Reported metrics
Tech debt fixes year-over-year improvement40%
Mean Time to Remediate (MTTR) security fixes63%
Developers onboardedmore than 1,000 developers in just one week
Lines of code acceptedover four million lines of code
Show all 5 reported metrics
tech debt fixes year-over-year improvement40%
Mean Time to Remediate (MTTR) security fixes63%
developers onboardedmore than 1,000 developers in just one week
lines of code acceptedover four million lines of code
developer satisfaction and NPS score4.4/5
Reported stack
GitHub CopilotGitHub Advanced SecurityCopilot AutofixGitHub
Source
https://github.com/customer-stories/cathay
Read source ↗

Frequently asked questions

What did this team achieve with this AI workflow?

Cathay achieved a 40% year-over-year improvement in tech debt fixes and a 63% decrease in Mean Time to Remediate security vulnerabilities, while rolling out GitHub Copilot to more than 1,000 developers in one week, ac…

What tools did this team use?

GitHub Copilot, GitHub Advanced Security, Copilot Autofix, GitHub.

What results were reported?

Tech debt fixes year-over-year improvement: 40%; Mean Time to Remediate (MTTR) security fixes: 63%; Developers onboarded: more than 1,000 developers in just one week; Lines of code accepted: over four million lines of code (source-reported, not independently verified).

How is this quality assurance AI workflow structured?

Developer coding request in IDE → Copilot code completion → Agent mode multi-step execution → Embedded security scanning → Copilot Autofix remediation → Developers ship secure code.

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