Advanced analytics with artificial intelligence isn't a project to be left wholesale to IT. It is a strategic business opportunity that requires technical know-how and organizational coordination. Companies making the transition to AI must build data and analytics into their core functions, an enterprise that requires careful change management and cross-cutting transparency.
Companies exploring big data and AI technologies often seek to use preexisting architectures, outside datasets, and off-the-shelf libraries. While these assets can be useful for purposes of exposition, rarely are they tailored to the specific challenges the business faces and the quality the business demands. Moreover, companies usually overlook the incredible store of untapped proprietary information they already possess:
- We first scope the strategic objectives a company wishes to serve with advanced analytics and AI.
- Next, we identify processes that present opportunities of the greatest value.
- After communicating the strategy, we provide the analytical and engineering rigor necessary implement them.
The use of appropriate scientific inference techniques to avoid spurious relationships is of paramount importance, which takes an experienced scientist to address. Our skilled team is prepared to support initiatives involving any number of methods, including supervised and unsupervised machine learning, predictive modeling, customer segmentation, and experimental design. Our development team is fluent in a multitude of industrial front-end and back-end languages, making integration and continued support seamless.