Applied Intuition is an Autonomy Software & Simulation company founded in 2017 and based in Mountain View, United States. It has raised $1.5B in total funding, most recently a Series F in 2025 at a $15B valuation.
| Date | Stage | Amount | Valuation | Lead investors |
|---|---|---|---|---|
| Jun 17, 2025 | Series F | $600M | $15B | BlackRock, Kleiner Perkins |
| Mar 1, 2024 | Series E | $250M | $6B |
| Lux Capital, Elad Gil, Porsche Investments Management |
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Unified simulation, data management, and validation toolchain for ADAS and autonomous-vehicle development used by automotive OEMs and autonomy programs. It enables engineering teams to build, test, and certify autonomy stacks at scale across simulation and real-world scenarios, generating edge cases, replaying logged drives, and measuring coverage. The platform is widely adopted across the AV industry as core infrastructure for safely developing and validating self-driving systems before deployment on public roads.
End-to-end autonomous driving stack combining a unified neural architecture with white-box transparency and a continuous data engine. Hardware-agnostic, it integrates across sensor suites, compute platforms, and vehicle architectures for passenger and commercial vehicles. Designed to achieve human-like driving behavior and scalable validation, the SDS lets OEMs and autonomy developers field a production driving system while continuously improving it through Applied Intuition's data and simulation toolchain.
Data management system that automatically extracts and indexes metadata from sensor logs, enabling large-scale search, curation, and scenario mining across petabytes of real-world and simulation data. It is foundational infrastructure for model training and fleet-wide safety analysis, letting autonomy teams quickly surface rare events and build targeted datasets. Basis is used by automotive OEMs and autonomy development teams to turn raw fleet data into the training and validation material that improves self-driving performance.
8 patents on file, but none with both an extractable figure and an abstract on Google Patents yet.