A fintech scale-up had built its product quickly on an older Python codebase that was now slowing them down. Deployments were risky, tests were sparse, and the aging framework version created security and compliance concerns. They needed to modernise without pausing feature delivery or disrupting a live, regulated service.
Python, Django, automated testing, CI/CD, cloud migration
We augmented their team with senior Python engineers and ran a modernisation programme in parallel with ongoing work. We upgraded the framework, refactored the riskiest areas, introduced a strong automated test suite, set up continuous integration and deployment, and migrated workloads to a more scalable cloud setup, all in careful, reversible steps.
We prioritised changes by risk and value, tackling the most fragile and security-sensitive parts first. Every change went in behind tests and CI so the live service stayed stable throughout, and knowledge was shared with the in-house team as we went.
Brought the platform onto a current, supported framework version, resolving security and compliance concerns.
Made deployments safe and routine with automated testing and CI/CD, replacing risky manual releases.
Improved performance and scalability through the cloud migration.
Upskilled the in-house team so the improvements stuck after the engagement ended.
Because the product was already Python and Django, modernising in place let the client keep their domain code and team knowledge while gaining stability, security and scale.
Let's discuss framework upgrades, automated testing, CI/CD, and cloud migration without pausing feature delivery on a live service.
