
AI Solutions
We bridge the gap between cutting-edge artificial intelligence and real-world automotive safety. By combining state-of-the-art foundation models with precision alignment and hardware-optimized edge deployment, we transform complex scene perception into reliable, real-time driving intelligence.
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Services & Solutions

Precision Alignment & Post-Training Support
A model is only as reliable as its training. We utilize advanced alignment techniques to ensure vehicle behavior is smooth, predictable, and safe.
• Develop Curated SFT Datasets: Supervised Fine-Tuning using high-fidelity, real-world data to anchor model performance.
• RLHF for Autonomous Safety: We deploy Reinforcement Learning from Human Feedback to align AI decision-making with expert human driving standards, significantly reducing false and erratic maneuvers.
• Edge-Case Envelope: Targeted data curation to solve the "long-tail" challenges of autonomous transit.

High-Performance Deployment at the Edge
Real-time safety requires millisecond-latency execution. We optimize the world's most powerful AI models to run natively on automotive-grade silicon.
• Hardware-Agnostic Optimization: Seamless deployment across NVIDIA DRIVE and Qualcomm Snapdragon Ride platforms.
• Advanced Toolchain Integration: Leveraging TensorRT and Qualcomm QNN to maximize throughput while maintaining strict power efficiency.
• KPI-Driven Results: Rigorous optimization to meet and exceed functional safety (ISO 26262) and accuracy targets without compromising on-vehicle compute resources.

ADAS Perception & Driving Policy
We bridge the gap between "seeing" and "understanding." By leveraging state-of-the-art Transformer and Vision-Language-Action (VLA) Foundation Models, our solutions move beyond simple object detection toward comprehensive scene intelligence.
• Discrete & End-to-End Architectures: Flexible integration of modular perception or unified E2E stacks.
• Foundation Model experience: Expertise in deploying proprietary and leading open-source models like Alpamayo and MindVLA to define sophisticated driving policies.
