A healthcare start-up’s platform had reached product-market fit, and growth had moved the goalposts. Enterprise clients now ran vendor security reviews the platform couldn’t yet pass, and its stack was approaching end-of-life. We modernized it without ever stopping the business: from zero automated tests to 95%+ coverage on the code that runs it, onto a supported stack, with MFA and a full audit trail. We name the metrics, not the client.
The Situation
Our client is a healthcare start-up whose web application runs the operation: it processes sensitive medical data, with operational automation, system-to-system integrations, and two-factor authentication on access. We had built the original platform, and it worked: it carried the product all the way to product-market fit, handling thousands of inquiries and hundreds of gigabytes of medical data a month.
Then growth changed what it had to be. Winning and keeping enterprise clients meant clearing their vendor security due diligence, and the earlier posture wasn’t built for that scrutiny. The stack itself was nearing its end-of-life cutoff, a hard support deadline rather than a preference, with security and maintenance debt compounding behind it. Access controls sat below what a platform handling medical data needs to clear such a review. And underneath all of it, a system carrying real clinical load had effectively no automated tests, on a codebase shaped to reach a market, not to be built on. We were brought back to modernize the live platform against that deadline, without stopping operations.
What We Did
The constraint set the method: modernize incrementally while the platform kept running, never a clean-slate rewrite.
The hard part of a job like this is the ramp-up: re-learning a codebase a couple of years old, built for speed rather than for the next team, before a single change can be made safely. AI-augmented delivery is what made that painless. It accelerated reading and mapping the existing system, drafting the test suite that had never been written, and working through the dependency upgrades, keeping the catch-up economical against a fixed deadline instead of letting it become the bottleneck.
We hardened the platform for the security reviews: multi-factor authentication, password rotation enforced every 30 days, and a full audit trail across the system, the access-control and traceability evidence a vendor security review asks for on medical data. We took the platform off its end-of-life stack, upgrading everything to supported long-term-support versions and dropping unused components, which cleared the deadline and shrank the maintenance and security surface at once. We built the regression safety net that wasn’t there, bringing core business logic and its views to 95%+ coverage each, from none. We Dockerized the environment and set up automated CI/CD, turning releases into a repeatable path. And we exposed a clean reporting API for the enterprise systems to consume results, leaving the platform more open than we found it.
What Moved
Underneath, the test numbers: 82% coverage across the repository and 95%+ on the business logic and views, from a starting point of none. The security posture is what the enterprise vendor reviews were asking for: MFA, 30-day credential rotation, and a full audit trail. The end-of-life deadline is cleared, the platform now on supported versions with dead components removed, and releases run through Docker and automated CI/CD. The scale figures, thousands of inquiries and hundreds of gigabytes a month, are reported by the client, not measured by us; that the modernization landed without interrupting any of it is the part we deliver.
Where It Went
None of it was a rewrite. The platform that won product-market fit is the same one now cleared for enterprise scrutiny: hardened in place, against the deadline, while it kept running.