This case study shows how SBL turns operational complexity into a governed digital operating model where workflow, data, quality and decisions can be managed together.
The institutional challenge
- Multi-sport requirements: Expertise needed across Soccer, Basketball, and American Football.
- High-volume operations: Requirement to annotate player bounding boxes for 3,900 matches.
- Tight Feedback Loops: Model improvement required constant, precise data iteration.
What SBL engineered
- Built a managed AI operations model with controlled intake, workflow routing, quality review and delivery governance.
- Combined automation with human oversight to handle scale, variation and exceptions.
- Used operational dashboards and repeatable quality controls to make the workflow measurable and improvable.
- Consult & Align: Requirement mapping and alignment on flexible annotation rules.
- Workflow Setup: Configuration of a 125-person dedicated annotation team.
How the work should be understood
SBL's role is not limited to executing a task. The value comes from understanding the operating workflow, engineering the data and automation layer, applying governance controls, and helping the institution move from manual dependency to intelligent, measurable operations.
