Action Description & Activity Recognition for Security-Focused AI Models

Video Annotation & Classification, Action Recognition Annotation, Human Activity Detection, AI Training Data Operations, Workforce Scaling & Management, Quality Assurance & Validation, Security & Surveillance Dataset Annotation, Human-in-the-Loop AI Support

The client required large-scale video annotation support for an Activity Recognition project focused on training AI models to identify security- and safety-related human actions. The project involved multiple iterations over approximately two months and required rapid workforce scaling to support continuously evolving annotation volumes and task requirements.

The project focused on identifying and classifying critical human actions within video datasets, including:

• Person assaulting another person
• Climbing over a fence, gate, or wall
• Falling on the floor

Due to the dynamic nature of the project, annotation jobs were delivered in large batches (over 10,000 videos per batch) and processed at a high pace, requiring continuous workforce coordination, operational flexibility, and rapid task allocation.

The client needed a reliable annotation partner capable of scaling quickly while maintaining throughput, responsiveness, and consistent quality across fragmented and continuously changing workloads.

Mindy Support was selected due to its ability to rapidly scale global annotation operations while maintaining operational flexibility and delivery consistency for enterprise AI projects.

Key advantages included:

• Fast workforce ramp-up capabilities
• Access to multilingual distributed teams
• Proven experience with large-scale AI data operations
• Dedicated operational management and QA oversight
• Ability to process dynamic micro-task workloads in near real time
• Scalable human-in-the-loop infrastructure for AI training projects

• Scaled and managed a distributed annotation workforce of approximately 40 – 45 FTEs throughout the project lifecycle
• Engaged a mixed workforce from India and Ukraine, supported by a dedicated operational management team to maintain throughput and delivery timelines
• Delivered high-volume action recognition and action classification services across multiple project iterations
• Maintained operational agility to rapidly assign and process micro-task annotation jobs in near real time
• Supported the client’s AI training objectives through structured annotation workflows and continuous quality monitoring processes

• Successfully supported high-volume project operations over a two-month period
• Processed and annotated more than 100,000 videos across multiple activity recognition categories
• Enabled rapid dataset turnaround despite fragmented task distribution and continuously evolving workloads
• Helped accelerate the development of AI models designed for safety, surveillance, and security-related event detection
• Demonstrated scalable workforce coordination and operational responsiveness for enterprise AI training initiatives