[ World Intelligence · APEX ]

Score and evaluate AV models
on real-world intelligence

APEX scores reaction time, anticipation, avoidance and confidence against real events your system has never seen, and reads how ready a given city is for it. Every definition is published before the run, so the score means the same thing to whoever reads it.

[ Who is APEX for ]

How can you use APEX?

There is still no driving test for an autonomous system, but APEX provides a readiness case a regulator can inspect.

01 / 03   Open use case

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AV program leads

Assembling a safety case.

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Safety case / four dimensions
[ Illustrative ]

02 / 03   Open use case

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Regulators

Who need more than an applicant’s own word.

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Published definitions / independent run
[ Illustrative ]

03 / 03   Open use case

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Cities

Deciding whether a system is ready for their streets.

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City readiness / street grid
[ Illustrative ]
[ The APEX scorecard ]

Is your AI ready to drive
in the real world?

Compare your autonomous system directly against the human behaviors it aims to understand.

Reaction Time

Quantify your stack’s reaction speed against average and high-performing human benchmarks in identical scenarios.

Anticipation

Measure predictive risk signals. Did the AV anticipate a hazard as effectively as a safe human driver?

Avoidance

Analyze danger-avoidance behaviors using our BADAS 2.0 model, trained on millions of near-miss events.

Confidence

Achieve statistical significance without driving billions of physical miles, using our massive historical corpus.

[ Contact ]

Talk to us about scoring AV models.

Join the developers, insurers, and regulators setting the new standard.

[ Contact us ]

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