This national trade association wanted to build a custom embedded analytics portal to improve data quality and access for their thousands of local associations across the U.S.
Our client’s new load and carrier search platform was running queries extremely slowly, causing customers to abandon searches.
This real estate investing company needed a lead qualification engine that would automatically evaluate properties, enabling them to make smarter and faster real estate investment decisions.
A manufacturing company wanted to use analytics to optimize their supply chain but first needed help with JD Edwards data transformation.
A private equity group’s finance team was looking for a way to streamline and scale the financial reporting process to reduce the time and complexity of reporting.
The Aptitive data science team built a high performing and computationally inexpensive Random Forest model to enable prediction analytics capabilities.