A Managed Labeling Team for First-Person Video AI Training

The Challenge

Action recognition models need video split into clean, single-action moments with consistent text labels. The work is large, repetitive and sensitive to guideline drift, which is why quality breaks when volume scales. The buyer needs predictable daily throughput, a format that passes its own QA, and a team that stays calibrated week after week.

What We Proposed

A managed team with its own leads, internal QC, delivery management and operations, running on the client’s annotation platform. Each video is divided into contiguous 2 to 5 second segments, one atomic action each, with no overlaps and no gaps. Every segment gets one imperative sentence in a Verb, Noun, Hand pattern, such as ’Grab cup with right hand’.

• Temporal segmentation of first-person video
• Atomic action text labels in a fixed English format
• Internal QC and format compliance before submission
• Daily and weekly throughput and quality reporting
• Rework of segments the client’s QA rejects

Key Design Decisions

Quality control sits in two places. Our internal QC spot-checks at least 10 percent of output before each submission, and the client keeps the formal QA audit, so we are never grading our own work. Format rules ban vague verbs and guessed intentions, and labels cover only what is visible in the frame. Team leads supervise at about one lead per 17 labelers.

• Ban on ambiguous verbs such as manipulate, adjust and move
• No intended actions or actions outside the frame
• Platform, hosting and video storage supplied by the client
• Recruitment, training and attrition backfill run by Nexora

Pilot First

The plan starts with a pilot on a small team. It measures real labeling speed and reject rate on the client’s own video before anyone commits to scale. A go/no-go review closes the pilot. Only then does the team ramp to the full throughput target, with ongoing calibration against the client’s guidelines.

What the Client Gets

A labeling operation with a stated daily volume, a defined label format, and reporting on pass rate, reject rate and productivity per labeler. The client avoids building a recruiting and management function for annotation. Nexora handles hiring, training and backfill, and the client keeps control of the guidelines and the final quality audit.