Feasibility prototype
Prove modernization is feasible — before you commit.
The scariest question in a mainframe move isn't “can it be converted?” — it's “will the modern system handle our volume and meet our SLAs?”We answer it with running, load-tested evidence in weeks — not a consultant's deck in months.
Why this exists
Performance is where modernizations die.
Mainframes deliver predictable, high-volume throughput with stable latency — that's what they're extraordinary at. A modern target canmatch or beat it, but only with the right architecture: the JVM's garbage collection and scheduling introduce latency variance and tail-latency risk that never existed on the mainframe. So the honest answer to “will it perform?” is “it depends — so measure it, early.”
Teams usually find out after years and millions are spent. A fast, running prototype turns that unknown into a number you can put in front of your risk team before you commit a budget.
How a feasibility sprint runs
Pick the hot paths
Your highest-volume transactions and your heaviest batch — the places where performance actually decides go or no-go.
Convert fast
Our deterministic engine produces a running modern version of those paths in days, not months — the speed is the whole point.
Deploy & load-test
We stand it up and drive it at your real peak volume, on production-like data — the way it will actually be hit.
Report — go or no-go
Throughput, p50/p99/p99.9 latency, batch-window timing, and a bottleneck map — plus a clear verdict and what it would take to meet your SLA.
What you get back
- →A running prototype you can see, run, and load-test yourself.
- →Throughput, tail latency (p99/p99.9), and batch-window numbers — at your volume.
- →A bottleneck map: exactly where the risk is (a datastore, a batch job, a few transactions).
- →A clear go / no-go, with the architecture changes it would take to hit your SLA.
- →The scenarios become your modernization test corpus — the work isn't throwaway.
What it measures — and what it doesn't
This proves whether your business logic, on a representative modern architecture, can meet your SLAs at volume — and it surfaces the bottlenecks early. It is not a claim that an auto-converted prototype equals final production performance: mainframe performance comes from the platform, and a production system is tuned and architected (caching, async, horizontal scale, the right datastore).
So we test against your business SLA, not the mainframe's raw numbers; correctness is unit-test level on a representative slice, with production-like data. If even a rough prototype already clears your volume, that's a strong green light. If it doesn't, you've found the bottlenecks cheaply and early — which is exactly the point.
Why it's different
Running evidence, not a deck
Most “feasibility studies” are portfolio analysis and a business case. We hand you a system that runs and a benchmark at your volume.
Fast and low-cost
Because our conversion is fast, we produce load-testable code in days — so feasibility costs a fraction of a hand-built proof of concept.
Honest go / no-go
We'll tell you if it won't work, and why. That candor — with the evidence behind it — is what makes the verdict worth trusting.
De-risk the biggest decision first
It's the lowest-commitment way to answer the question your board will ask — and everything you build flows straight into the full modernization.