Proof, Not Promise
A worked reference conversion, validated field-by-field against a live Mule 4 runtime.
This is our own reference application, not a customer engagement — we're onboarding our first pilot partners now. We publish it so you can see exactly how Proven-Parity Migration works before you send us anything.
Reference conversion: a real Mule 4 app
A Mule 4 application exercising HTTP listeners, MySQL (select, insert, bulk-insert, delete), file operations, DataWeave transforms, caching, and flow control. We convert it to Spring Boot, deploy it alongside the original, and replay the same Postman collection against both — then compare every response field.
GET /db✓ MATCHPOST /db-insert✓ MATCHPOST /db-bulk-insert✓ MATCHDELETE /db-delete✓ MATCHGET /file-list✓ MATCHcore endpoints byte-identical to Mule
Verified against real infrastructure — not mocks
Connector families are converted and run against their real backing service, then response-compared. No stubs, no scaffolding.
Core web / data / file / object-store families are diffed against a live Mule runtime; message and cloud families are verified against their real services via Docker and LocalStack.
What We Don't Hide
The only responses that don't exact-match are the ones that legitimately can't between two independent runs — timestamps, generated IDs, live third-party API data, and cache age. We show those, score them on shape and type instead of exact value, and report the deterministic-endpoint match rate separately, so the number reflects real logic parity, not run-to-run noise.
1,267 engine tests · 457 converter tests · 0 failures · ~80% memory reduction vs the Mule runtime
Run It On Your App
The fastest way to evaluate any of this is on your own code. Send us one Mule application and your Postman collection, and we'll return the converted Spring Boot project and the same field-by-field parity report — on-premise, inside your environment, if you prefer. About two weeks. You keep everything, either way.