Today we are publishing the head-to-head case study that resulted in our first seven-figure CAE renewal being retired. The customer — a mid-sized aerospace prime — completed a two-quarter pilot across twelve real production cases. Aether matched or beat their incumbent commercial CAE stack on ten of twelve cases, was within 3% on the other two, and finished the campaign in 38% of the wall-clock time at iso-accuracy. The prime retired the $1.8M three-year renewal at quarter-end.
The pilot ran the standard Apex engagement model. Cases were chosen by the customer's CAE lead from their actual production workload — five external aerodynamics studies, three crash and impact simulations, two electromagnetic compatibility analyses, and two coupled fluid-structure cases on a rotor stage. Seven cases had measured wind-tunnel or wind-on-rig data; the remaining five had production telemetry. Mesh budgets, time-step budgets, and turbulence-model family were matched between Aether and the incumbent stack. Solver settings were tuned independently for each tool by the engineers familiar with that tool — we did not handicap the baseline.
Result tabulation was blinded. The customer's CAE lead recorded pass/fail per case without knowing which tool had produced which prediction. We have used the same blinding protocol across our published benchmark comparisons; in our experience it is necessary to get a clean head-to-head, and the customer's lead was the one who insisted on it during pilot kickoff.
The clearest wins came from the coupled fluid-structure cases on the rotor stage. Aether solved fluid and structural together on a single mesh; the incumbent stack required two solvers, an inter-tool import step, and a manual time-step matching pass. The model not only finished faster — it produced a closer agreement to the rig measurements at the trailing edge, where the inter-tool import previously introduced a small but consistent offset that the prime had been carrying as a known quirk for over a decade.
The aerodynamic cases were a more modest win. Aether produced lift and drag polars within 0.6% of measured values across the angle-of-attack range; the incumbent produced 1.1%. Both are competitive results in absolute terms; the margin matters mostly because the prime's iteration cycles compound the difference into hundreds of design-exploration runs per programme. On the crash cases, Aether matched the incumbent on peak deceleration and on integrated impulse, and beat it modestly on local strain concentration in the regions the prime's gauges sampled.
Two cases came back as a wash — an EMC study at low frequency and a high-Reynolds external flow on a familiar geometry — with no clear winner. The prime's existing methodology and engineer hours dominated; either tool would have done the job. These cases are useful in two ways. They grounded the pilot — we did not claim a sweep. And they argued against ripping out the incumbent stack for everything; the prime kept a residual licence count for cases like these where the cost of switching was not justified by the marginal accuracy gain.
Three things happened at the customer at quarter-end. First, the renewal letter was sent back unsigned. The incumbent's account team escalated; the prime's CFO held firm because the technical evaluation was clear and the renewal cost was material. Second, the prime consolidated their CAE team's licences down to a small residual seat count — approximately 12% of the previous total — for the niche tools Aether doesn't yet cover. Third, the prime redirected the freed budget to a new hypersonics R&D programme, which is now also running on Aether using the platform's hypersonic CFD capability.
What we learned about pilot methodology. First, blinding the result tabulation matters. The prime's CAE lead's first informal pre-pilot view was that the incumbent was probably better, given the decade of methodology investment; the blinded outcome was the opposite. Second, pair forward-deployed engineers with senior engineers from the customer rather than with the customer's evaluation lead — the senior engineers carry the methodology knowledge that matters during edge cases. Third, the post-processing UI matters more than we expected; we have invested substantially in the studio surface since this pilot in response to engineer feedback.
The customer has approved this publication. The full case study, with the methodology, the per-case numbers, and the customer's quote, is open at /customers/aerospace-prime-cae. The reproduction discussion is at /research/retiring-cae. The cases themselves — anonymised geometries, meshes, agent traces — are available on request under NDA.
This is the first of several similar engagements we expect to publish over the next year. We are deliberately not naming the customer in the headline release; the customer-controlled case-study page will link from /customers when they make their identity public. For customers running similar evaluations: the pilot programme is documented at /pricing; the engagement model is described in detail on the customer-stories index.