Pilotier provides a camera‑first autonomous driving software stack that uses deep‑learning models to generate semantic maps, depth estimates, and object trajectories from raw video, eliminating the need for LiDAR or radar. The SDK includes a real‑time inference engine optimized for automotive GPUs, ROS2‑compatible APIs, and an Unreal Engine 5 simulation suite for virtual testing, enabling OEMs and fleet operators to develop and certify Level 5 vision‑centric autonomy.
Funding
Funding not disclosed
Founders
Product
Problem
Current autonomous vehicle platforms rely heavily on expensive LiDAR and radar arrays, leading to high hardware costs and complex sensor integration. Achieving full SAE Level 5 autonomy also demands transparent perception pipelines that can be validated against human visual cognition, which many existing solutions lack.
Solution
Pilotier delivers a camera‑first autonomous driving software stack that processes raw video streams from vehicle‑mounted cameras using deep‑learning perception and motion‑estimation models. The platform replicates human visual perception to generate dense semantic maps, object trajectories, and scene understanding without auxiliary sensors. Its end‑to‑end architecture provides deterministic, auditable decision outputs, supporting safety certification and debugging. The stack is packaged as a modular SDK with real‑time inference optimized for automotive GPUs, enabling OEMs and fleet operators to integrate vision‑centric autonomy into existing vehicle platforms. Pilotier also supplies a high‑fidelity simulation environment built in Unreal Engine 5 for virtual testing and validation before road deployment.
Target Audience
The primary customers are automotive OEMs and large fleet operators developing Level 5 autonomous vehicle capabilities, as well as Tier‑1 suppliers seeking a vision‑centric perception stack for integration into their platforms.
Features
- Deep convolutional neural networks for real‑time semantic segmentation, depth estimation, and 3D object detection directly from monocular or stereo camera feeds
- Motion‑estimation module that fuses optical flow and ego‑motion to predict object trajectories with sub‑meter accuracy
- Transparent decision pipeline with explainable AI visualizations and deterministic rule‑based safety layers for auditability
- Automotive‑grade inference engine optimized for NVIDIA DRIVE and other embedded GPUs, delivering < 30 ms latency per frame
- Full SDK with ROS2‑compatible APIs, sensor‑fusion hooks, and over‑the‑air update capability
- Integrated Unreal Engine 5 simulation suite (SLED) for scenario generation, sensor modeling, and closed‑loop validation
- End‑to‑end encryption and ISO 26262‑aligned software development lifecycle for functional safety compliance