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Enterprise software company · Technology & Digital Platforms

Software Firm Halves Legacy Modernization Backlog

A software company put repository-grounded engineering intelligence to work on a decade-old codebase—accelerating understanding, testing, and migration without sacrificing review.

-50%modernization backlog age
3xfaster test coverage expansion
0unreviewed automated merges

About the client

An enterprise software company with a flagship product carrying ten-plus years of accumulated engineering decisions, a growing modernization backlog, and hiring that could not keep pace with onboarding time.

The challenge

A core product carried ten years of undocumented decisions. Senior engineers spent weeks onboarding onto unfamiliar modules, and modernization stalled because understanding the code cost more than changing it. Test coverage on legacy modules was thin enough that every refactor was a leap of faith, and the engineers who understood the deepest corners of the system were the ones closest to retirement.

The engagement

Global AI Nexus grounded an engineering copilot in the repository, tickets, and runbooks—so code understanding, test generation, and migration drafting all cite the actual codebase rather than generic patterns.

Every automated contribution lands as a reviewed pull request; nothing merges without human approval.

Onboarding became the proving ground: new hires worked real modernization tickets with copilot support from week one, and the measured difference between copilot-assisted and unassisted throughput set the rollout case for the wider engineering organization.

In their words

The copilot doesn’t write our code—it reads it, so we don’t have to re-read it. Ten years of decisions finally became searchable, citable context for every engineer, not just the two who were there.

VP Engineering, Enterprise software company

The results

  • 01The modernization backlog’s median age halved in six months.
  • 02Test coverage expanded 3x faster than the manual baseline.
  • 03New-hire onboarding to first meaningful commit dropped from weeks to days.
  • 04Review quality held—zero unreviewed automated merges.
  • 05Institutional knowledge about the legacy system now lives in the copilot’s grounded context, not in departures.

GAINX systems deployed

The solution systems behind this outcome.

01

Generative AI Engineering

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02

Enterprise AI Systems

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