Sep 17, 2025
Paradym Switch: Early Evidence from Four Projects
In a preliminary review of four legacy modernisations, Paradym Switch delivered the same scope for roughly 70 percent less cost and in roughly 70 percent less time than a commercial estimate for the equivalent work using traditional, non-AI methods. The sample is small and the findings early, but the effect is consistent across every project.
How we measured it
The review compares two figures for each project. The baseline is a commercial estimate of the time and cost to deliver the modernisation with traditional, non-AI methods. The comparison is the actual time and cost recorded on our platform, for work completed or currently in hand. The four projects span distinct domains and technology stacks, from Java, C, C++ and Progress OpenEdge systems to modern stacks on React, .NET, Azure and AWS. That spread reduces the chance the result reflects a single language, sector or architecture.
Roughly 70 percent less time and cost
The reductions are large and consistent. Estimated delivery time fell by 67 to 79 percent and estimated cost by 67 to 77 percent. A project estimated at three to four years was delivered in nine to twelve months. No project fell outside the range, and within each one the proportional savings in time and cost moved together.
For a finance leader, the implication is direct. Faster delivery does not only lower the build cost; it shortens the period of running two systems in parallel, brings the benefits of the new platform forward, and reduces the exposure that comes from depending on an ageing stack. The compression of the timeline is, in many cases, worth as much as the cash saving itself.
Why the savings are substantive
The result tracks where modernisation effort traditionally concentrates: understanding the legacy system, rebuilding its logic on a new stack, and testing the outcome. Our platform compresses the first two through AI-assisted analysis and code generation, while keeping human discovery and review in the loop so the rebuilt system preserves the business logic customers depend on. The saving comes from accelerating the labour-intensive stages, not from removing the controls that protect quality.
How to read these numbers
This is a preliminary review of four projects, not a controlled trial. The baseline is an estimate rather than a parallel build and cannot be observed directly; the projects vary in scale and complexity; and some platform figures cover work still in progress. Read the numbers as directional early evidence of what AI-assisted modernisation can achieve, with outcomes varying by the size and condition of the system.
Frequently asked questions
What is the time and cost comparison based on?
For each project, a commercial estimate of delivery using traditional, non-AI methods is compared with the actual time and cost of delivery on our platform, for projects completed or currently in hand.
How large were the observed savings?
Across the four projects, delivery time and cost each fell by approximately 70 percent, with per-project reductions of between 67 and 79 percent. The figures are preliminary and will depend on the size and condition of the system being modernised.
About this study: figures derive from four Paradym Switch modernisation projects, completed or in hand. Traditional, non-AI figures are commercial estimates for the equivalent scope; platform figures are actual time and cost recorded. Findings are preliminary.
