Deepen AI, a full-stack data lifecycle platform for autonomous vehicles (AVs) and robotics, is spotlighting new platform capabilities at CES 2026 aimed at improving sensor fusion reliability, reducing calibration friction, and scaling deployment in safety-critical environments.
As autonomous systems move from controlled pilots to real-world industrial and public deployment, developers face higher standards for repeatability, validation, and auditability. Deepen AI’s platform addresses these challenges across the full data lifecycle, from annotation and sensor fusion to calibration and validation, giving teams confidence when operationalizing AVs and robotics at scale.
CES Highlights: Live Demos and Exclusive Previews
At LVCC, West Hall, Booth 3161, Deepen AI will showcase practical, hands-on capabilities for real-world autonomous workflows:
- Targetless Calibration (Live Demo): Visitors can adjust sensor positions and watch the platform automatically align multiple sensor modalities, reducing downtime, complexity, and calibration errors—a critical improvement for field-deployed AVs.
- Vision-Language-Action (VLA) Framework (Exclusive Preview): A first look at Deepen AI’s upcoming VLA framework, which integrates multi-sensor data with higher-level reasoning and action planning for autonomous robotic systems.
- Safety Pool™ Integration with World Foundation Models (Expanded): Deepen AI’s scenario library, designed to support testing and safety assurance, now leverages leading foundation models for richer, more realistic simulation data.
Why It Matters
“Autonomy doesn’t scale on demos; it scales by addressing as many real-world scenarios as possible,” said Mohammad Musa, Founder and CEO of Deepen AI. “At CES, we’re showing teams the tools they need to deploy safety-critical systems reliably—from targetless calibration to next-generation autonomous workflows using Vision-Language-Action models.”
Deepen AI’s momentum reflects a broader industry shift: as AV and robotics programs expand from pilot programs to regulated deployments in mobility, logistics, manufacturing, and mining, the bottleneck increasingly lies in data lifecycle management, calibration, annotation, validation, and auditable safety assurance. Platforms like Deepen AI are emerging as critical infrastructure for scaling autonomous systems with confidence.
Power Tomorrow’s Intelligence — Build It with TechEdgeAI
