Artificial intelligence is commonly misunderstood as a technology that will bring omnipotent capability to machines. In reality, it is a technology that radically improves the ability of machines to make predictions. It's our job as data scientists to turn those predictions into actionable judgements, and doing so 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 artificial intelligence or advanced analytics.
- Next, we identify processes that present opportunities of the greatest value.
- After communicating the strategy, we provide the engineering and analytical rigor necessary to implement it.
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.