
Closing the AI-to-production gap: 70% faster development, quality intact.
A Fortune 500 workforce solutions provider that processes millions of benefit claims a year needed to deliver faster without weakening compliance or security.




All results come from a controlled pilot, not a full production rollout.
AI wrote code faster. Delivery did not speed up.
AI coding tools were producing code faster, but end-to-end delivery time stayed flat because testing, security checks and deployment could not keep up.
- QA overload. Test creation fell far behind AI-generated code.
- Security delays. Periodic manual scans could not match commit frequency.
- Deployment friction. Release gates were built for a slower pace.
- Compliance demands. Every change needed an audit trail and documented approval.
- Low error tolerance. Incorrect benefit calculations carry regulatory and reputational risk.
A four-step governed pilot.
- 01
Find failure points
Map where workflows would break under AI-accelerated volume, starting with QA, security scanning and provisioning.
- 02
Design governance
Build controls mapped to the client's specific regulatory obligations.
- 03
Embed in real work
Put AI tools into live IDE, CI/CD and provisioning processes, not sandboxes.
- 04
Validate and scale
Produce measurable, repeatable results that support a wider rollout.
Four areas, governed end to end.
AI coding assistants
Standard prompting patterns and code conventions, with human review of architecture and complex logic.
AI-assisted testing
Playwright test generation and coverage-gap analysis, scaled to code output.
Automated security scanning
Continuous scanning in CI/CD with compliance-aligned rules and automatic audit trails.
Infrastructure as code
AI-generated IaC with governance guardrails and human approval at release points.
By the numbers: traditional vs governed AI.
| Area | Traditional | AI-assisted, governed |
|---|---|---|
| Complex feature development | ~10 days | ~3 days |
| Infrastructure provisioning | ~4 hours | ~1 hour |
| Test case creation | ~2 days | ~2 hours |
| Automated test coverage | ~40–50% | ~86% |
| Security and quality controls | Manual and periodic | Built into CI/CD, no regressions observed |
More AI case studies.

Close your own AI-to-production gap.
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