TISC builds AI-powered video search tools that go beyond frame‑by‑frame analysis to understand intent, reactions, and events over time. Their agentic video engine autonomously scans and interprets sports footage— from single clips to full seasons—surfacing the moments that matter for faster decision‑making in courts, fields, and command centers.
Funding
Funding not disclosed
Founders
Product
Problem
Large volumes of video footage in sports, security, and command‑center environments are difficult to search and analyze because traditional AI models focus on individual frames rather than understanding sequences of actions and intent.
Solution
TISC offers an AI‑driven video search platform that autonomously scans and interprets video streams to identify moments of interest. By training foundation models with reinforcement learning and synthetic data, the system develops spatial‑temporal reasoning that captures intent, reactions, and dynamic events across time. The agentic video loop continuously looks, interprets, decides, and repeats, surfacing only the relevant clips for the user. This enables real‑time decision support and human augmentation, turning previously unsearchable footage into actionable knowledge for faster, more informed decisions.
Target Audience
Primary customers are sports analysts, security operations centers, and command‑center teams that need rapid, accurate insights from extensive video archives and live feeds.
Features
- Agentic video loop that autonomously navigates video, extracts and presents key moments without manual tagging
- Spatial‑temporal reasoning engine that understands sequences, intent, and reactions across frames
- Synthetic data generation pipeline that creates labeled reasoning traces to continuously improve model performance
- Reinforcement‑learned foundation models optimized for physical‑world video understanding
- Real‑time decision support interface for live footage, single clips, full games, and season‑long archives