D2iQ provides an independent platform for Kubernetes, an increasingly popular open-source container-orchestration system used for automating computer app deployment, scaling and management. The company's most disruptive product, D2iQ Kaptain, is a cloud native platform for running Machine Learning workloads on Kubernetes while accelerating the deployment of ML models. In short, D2iQ reduce the timeline from prototype to production for ML projects.
With the machine learning market size expected to hit just under $97 billion in 2025, having accounted for just $7 billion in 2018, there’s an onus helping enterprises from single-machine prototype to scalable product deployment quickly and successfully. The latter point may seem obvious, but it's worth noting that currently around 90% of all ML projects never make it into production.
What sets D2iQ, and its products, apart is that it allows data scientists to manage their machine learning models on Kubernetes without any applicable knowledge of Kubernetes itself. With a client list which includes T Mobile, Tommy Hilfiger, Verizon, BMW, and the US Air Force, coupled with impressive funding, D2iQ appears to have put itself in a strong early position.
Kirsty
Company Specialist at Welcome to the Jungle