Businesses fail to apply machine learning (ML) to produce bottom line business value. In fact, only 15% of models end up in use in day-to-day business. Wow right? We have set out to solve for this industry problem.
ML is not "new science", it has been in practice since the 1940s. What is new, is operating this technology at scale in today's dynamic and demanding technology landscape.
Organizations fail to put machine learning into practice due to the challenges of "operationalizing" the models. 9/10 businesses lack best-in-class cloud architecture and are void of an operating model for ML. This is critical to integrate and scale the technology in applicable business settings.
To be successful at ML you need to develop MLOps capabilities — that is, combine best-in-class cloud infrastructure, best practices, and an operating model for your team. This is where we shine.