Evercoast: Multimodal Data for Robotics & Simulation Teams | DataTribe Challenge 2025 Finalist Pitch скачать в хорошем качестве

Evercoast: Multimodal Data for Robotics & Simulation Teams | DataTribe Challenge 2025 Finalist Pitch

Recorded at Cyber Innovation Day 2025, which features the 8th Annual DataTribe Challenge as its marquee competition, where five exceptional cyber startups take the stage after weeks of hands-on coaching. As finalists, they represent some of the most promising emerging technologies in cybersecurity, gaining exposure to leading investors, industry executives, and strategic partners while showcasing their breakthrough innovations. Evercoast (2025 DataTribe Challenge Winner) introduces a platform that teaches AI how the physical world works: a Spatial AI engine that fuses multimodal sensor data into coherent, simulation-ready models, enabling robotics, AI, and cyber-physical systems teams to cut development cycles, improve real-world accuracy, and strengthen system resilience. Learn more: Website: https://cid.datatribe.com LinkedIn:   / datatribe-   Chapters 00:00 – Intro: The need for real-world data in physical AI 00:40 – The shift toward physical AI and industrial impact 01:30 – The data gap: Why physical AI lacks internet-scale datasets 02:20 – Multimodal sensor proliferation and integration challenges 03:30 – Introducing Evercoast: A platform for unified physical-world training data 04:20 – Sensor fusion: Spatial calibration, temporal sync & physics-rich data 05:10 – Customer examples: Air Force, Accenture, DOE, Hinge Health & research labs 06:00 – Business model: On-prem SaaS, cloud inference, dataset API 06:50 – Growth path: Land-and-expand, usage-based cloud, data network effects 07:40 – Technical foundation: Spatial ML, computer vision & simulation expertise 08:30 – Team background and prior founder experience 09:10 – Funding goals & scaling roadmap 09:50 – Judges Q&A #DataTribe #DataTribeChallenge #CyberInnovationDay #Cybersecurity #AI #SpatialAI #Robotics #Simulation #MultimodalData #MachineLearning #Innovation