Automated Brand Exposure Measurement
National Insurance Provider
Automated detection and measurement of brand logo appearances during live sports broadcasts.
Measuring sponsorship ROI from sports broadcasts required analysts to manually scan hours of footage to count logo appearances and estimate screen time. Reports took days to compile and missed a significant percentage of exposures, making it difficult to accurately value sponsorship deals.
A fine-tuned Moondream model detects brand logos in broadcast footage with high precision. Trained with SFT and RL on branded sports imagery, the model accurately identifies logo instances across varied camera angles, lighting conditions, and partial occlusions that the base model consistently missed.
- Logo detection F1 improved from 0.17 to 0.91
- Automated processing of full broadcast footage in near real time
- Reduced sponsorship reporting turnaround from days to hours
- Enabled per-second exposure tracking for accurate ROI calculation
Complete Vision AI Stack
This solution uses Moondream's integrated stack from model training through production deployment. Every layer is designed to work together, so you go from problem to deployed system without stitching together tools from different vendors.
AI Model Layer
Base Model
Moondream 3
Fine-Tuning
SFT + RL via Lens
Production Model
Moondream 3 (fine-tuned)
Deployment Layer
Inference Engine
Photon
Target Hardware
NVIDIA L40
Deployment
Cloud
Training Method
RL
Training Steps
139
Task Type
detect
F1
38.5% → 100%
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