Henry Schein
Delivered automated MLOps pipelines on GCP, achieving measurable improvements in forecasting accuracy, supplier lead time prediction, and customer inquiry response time, resulting in significant operational efficiencies and cost savings.
Conservative Savings:
$400K annually.
Nike
Amia.ai implemented a Generative AI product-tagging system using a RAG architecture. This improved tagging accuracy while reducing the need for manual checks, integrating seamlessly with Nike’s existing product workflows.
Conservative Savings:
$600K annually.
Indeed
Amia.ai built robust data engineering pipelines and insightful dashboards, enabling targeted marketing strategies and comprehensive revenue analysis for a leading job board platform.
Conservative Savings:
$200K annually.
Amgen
We developed and deployed machine learning models to refine demand forecasting and inventory optimization in Amgen’s pharmaceutical supply chain. These efforts minimized stockouts, cut waste, and improved overall operational planning.
Conservative Savings:
$1M annually
EBay
We developed machine learning and deep learning models to predict whether a consumer would return as a customer, while also creating an automated system to manage average handling time (AHT) for customer service.
Conservative Savings:
$400K annually.
Gilead
At Gilead, we implemented AI/ML models for global demand forecasting, supply chain optimization, and revenue projections. These data-driven insights supported CFO-level decision-making and more precise budget allocations.
Conservative Savings:
$800K annually.
