Case Studies
Oil Terminal Inventory Imbalance Prediction
Oil & gas firms have a tremendous opportunity to refresh demand forecasts with ML techniques, improving accuracy and adding to the bottom line.
Oil & gas firms have a tremendous opportunity to refresh demand forecasts with ML techniques, improving accuracy and adding to the bottom line.
In this whitepaper, we examine how different companies can attack the dispatch routing optimization problem using ML & AI.
Utilizing AI techniques like NLP is a great way to reduce the time it takes to find optimal candidates for job openings.
Being able to accept machine learning outputs in the decision making process is critically important, especially in Air Traffic decisions.
Anomaly detection is a great technique to use in supervised machine learning and AI applications.
Sometimes in ML & AI development, a data scientist will need to go and find external data sources to complement the modeling efforts.
We built a custom demand forecasting model using ML techniques, helping a leading professional services firm predict office bandwidth requirements.
Mosaic built a custom pricing system powered by artificial intelligence that recommends prices for 150M SKUs.
The Energy industry holds multiple predictive analytics and data science opportunities. One large utility hired a management consulting firm to study their data process. The management consultants identified over $300 Million of value by utilizing the data this utility had already collected over many years.
Manufacturing companies have a large opportunity to apply data science techniques like AI & ML to optimize their business processes.