Starseer: AI Exposure Management | DataTribe Challenge 2025 Finalist Pitch скачать в хорошем качестве

Starseer: AI Exposure Management | 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. Starseer introduces a platform that enables AI system builders to reduce risk and improve resilience before deployment by treating AI systems as probabilistic ecosystems—analyzing models, training data, refinement steps, and surrounding libraries and architectures to surface exploitable weaknesses and operational risks, ensuring production systems are safer and more reliable. Learn more: Website: https://cid.datatribe.com LinkedIn:   / datatribe-   Chapters 00:00 – Intro: Why AI systems need exposure management and assurance 00:40 – Founder background: AI security and red teaming at Verizon 01:20 – The problem: Uncontrolled AI adoption, shadow AI & operational risk 02:10 – AI usage policies: Approved services & reducing shadow AI 03:00 – Why AI is a “black box” for security teams 03:40 – Market focus: Credit unions, regional banks & regulated industries 04:30 – Starseer platform overview: Managing AI models, agents & datasets 05:20 – Enforce: Guardrails, gateways & usable security controls 06:10 – Assurance: Interpretability engine & model forensics 07:10 – Differentiation: Mapping model behavior + runtime understanding 08:00 – Deployment model: On-prem, GPU-aware, containerized, SaaS-capable 09:00 – Competitive landscape & positioning 09:50 – Early market engagement, GTM & pricing 10:30 – Judges Q&A #DataTribe #DataTribeChallenge #CyberInnovationDay #Cybersecurity #AI #AISecurity #AIExposureManagement #ModelSecurity #Interpretability #AICompliance #Innovation