Valgo

Quantify safety risks and establish human crash baselines for autonomous vehicles

Pricing model

Demo

Time to value

Requires Expertise

You can use Valgo to quantify safety risks and validate physical autonomous systems like robotaxis and robotrucks. It models failure probabilities and establishes human crash baselines so developers and insurers can benchmark autonomous vehicle safety against human driving standards. The system applies probabilistic inference, rare-event discovery, and failure sampling algorithms to identify critical operating failure modes in black-box autonomous stacks. This allows engineering teams and insurance providers to assess deployment safety, satisfy regulatory requirements, and ensure autonomous fleets operate safely in real-world scenarios.

What Valgo does

Compute human crash-rate baselines across operating domainsSample rare failure events using generative modelsRun Bayesian safety evaluations on black-box systemsAnalyze perception system failure trajectoriesGenerate safety validation reports for regulatorsClassify collision modes using principal component analysisEvaluate closed-loop vehicle decision-making policiesCalculates human crash baselines for autonomous vehiclesEstimates failure probabilities for black-box autonomous systemsDiscovers rare-event failure modes in commercial autonomy stacksApplies diffusion models to sample realistic failure scenariosProvides specification-curve analysis across diverse baseline metricsIdentifies root-cause timesteps that trigger vehicle collisionsEvaluates safety-critical perception and planning systems under uncertainty

Pricing breakdown

Pricing model: Book a demo

Frequently asked

ROS (Robot Operating System), AWS S3 (Data Ingestion), Azure Blob Storage, NVIDIA DRIVE Sim, Applied Intuition, Custom Telemetry APIs, AWS S3, Foxglove, Gazebo

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