Portfolio and Success Stories
Real-world AI solutions delivering measurable results
Bayesian Marketing Mix Modeling for Global Fashion Retailer
Global Fashion Retailer (NDA)
The client faced significant inefficiencies in allocating their annual marketing budget of US$ 3MM distributed across 17 different channels. Their last-click attribution system over-estimated lower-funnel channels by up to 250%, generating approximately US$ 700K annual waste on saturated Display. Additionally, they lacked visibility on adstock effects and channel interactions, resulting in decisions based more on intuition than causal data. They needed to reduce daily prediction error (MAPE) below 15% and create a budget optimizer that could run in less than 90 minutes for weekly planning.
Flight Delay Prediction using Advanced Machine Learning
International Airline (NDA)
The airline faced significant losses estimated at US$ 40MM annually due to flight delays, generating additional operational costs, passenger compensation and reputational damage. Traditional prediction methods showed poor performance (F1-score < 0.55), and did not adequately capture route-specific, time-specific or seasonal delay patterns. They also lacked capacity to identify anomalies or cluster delay types to implement differentiated strategies. The goal was to reduce delay-associated costs by at least 5% through accurate predictions that would allow preventive measures to be taken with sufficient advance notice.
Automated Poker Card Detection System
Online Poker Platform Operator
The client needed to identify and classify poker cards in online screenshots with over 95% accuracy to process large volumes of hands. The challenge included variability across 16 visual styles, occlusions in 9-player tables, resolutions from 720p to 4K, compression degradation and confusion between similar symbols (8/B, Q/K) that generated >15% errors with generic models. Additionally, the system needed to work in real-time (>15 FPS) on standard hardware and automatically adapt to new platforms without retraining.
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