SpaceX-Born AI Test Software Powers Electric Aircraft's First Flight

Aviation Week reported on September 14 that Sift, a software company founded by former SpaceX engineers including CEO Austin Spiegel, supplied the data-unification platform behind Heart Aerospace's electric X1 demonstrator, whose first flight took place in August 2026. The platform consolidates telemetry from ground testing, preflight checks, high-speed taxi runs and flight operations into a single system, replacing the fragmented mix of files, databases and tools such as MATLAB and LabVIEW that aerospace engineering teams have historically relied on.

For Heart Aerospace, Sift supported airframe, powertrain and actuator testing, as well as structural load testing on the wings ahead of the X1's first flight. The platform made post-flight telemetry immediately available for analysis: while the IADS system handled direct flight support, other engineers used Sift to review data and compare in-flight conditions against earlier ground and structural tests.

Spiegel spent more than five years at SpaceX building internal software that centralized data across simulations, component tests, integrated vehicle testing and operations — letting engineers reuse the same analytical tools throughout a program's life. Sift is a commercial version of that same model, now sold to aerospace developers who never built an equivalent internal system of their own. The company is also adding AI features, including an interface that lets engineers query telemetry and compare results across test runs in natural language, with longer-term plans for AI agents to assist with root-cause analysis of flight anomalies.

Cardan-AI angle: the notable fact here is not the software category — flight-test data platforms are not new — but where the capability originated and where it is now landing. A tool built to run one of the most demanding, highest-cadence hardware-test programs in the world is being resold, largely unchanged in principle, to an electric-aircraft developer with a fraction of SpaceX's scale and testing history. That is a textbook case of a testing discipline moving from tacit, firm-specific know-how to a purchasable product — a shift the accompanying analysis on cardan-ai.com examines through the economics of knowledge codification.