Iguazio Partners with Pure Storage to Operationalize AI for Enterprises
NEW YORK, Oct. 26, 2021 -- Iguazio, the MLOps (machine learning operations) company, today announced that it has become a Pure Storage technology partner. The new partnership will empower enterprises to unlock the value of their data and bring data science projects to life in an efficient, automated and repeatable way.
Together, Iguazio and Pure Storage empower enterprises to continuously roll out new AI services by adopting a production-first mindset using technologies which later allow them to scale with AI. By providing enterprise grade capabilities around data management, scale and performance and a layer of abstraction and automation, enterprises can start to focus on their business applications and not the underlying infrastructure.
“Many of our customers are seeing the enormous potential for AI-driven innovation, so we strive to provide our customers with the tools and infrastructure they need for the next step of AI” said Grace Chung, Director, Strategic Alliances, Analytics at Pure Storage. “We’re excited to help Pure and Iguazio’s join customers unlock the value of their data with an agile MLOps solution where compute and storage scales along with the needs of the business”.
“Most organizations starting out with AI initially focus on research and model development, because that is often seen as the natural first step to the data science process”. Commented Asaf, Co-Founder and CEO of Iguazio. “However, in order to effectively industrialize AI, enterprises need to think about the components they will need once they are running their AI applications in production at scale - as early on as possible. Together, Pure and Iguazio provide a complete MLOps solution with enterprise grade data management capabilities, providing the necessary building blocks to efficiently and cost-effectively support diverse and growing AI use cases which fuel business growth”.
With the new partnership, Iguazio offers an MLOps platform that automates and accelerates machine learning (ML) and deep learning (DL) pipelines. Its serverless and managed services approach shifts the focus from managing a sprawl of Kubernetes resources to delivering a set of higher-level MLOps services, over elastic resources, therefore reducing significant capital and operational costs, and accelerating time to market. Pure provides enterprise grade data management capabilities and products that are optimal for the challenges of data science, built for speed and simplicity at scale.
For deep learning use cases, requiring analysis of images or video at scale, unstructured data can be organized in files or objects (on Pure FlashBlade) and accessed directly by the applications. For machine learning use cases, Iguazio’s real-time feature store, which is built into the MLOps platform, can access structured data on high-performance, low-latency NVMe storage using Pure FlashArray. The Pure Portworx Kubernetes-native storage solution supports the persistence needs of stateful micro-services. This solution is available across all major cloud providers, on-premises or in hybrid environments.
Both Pure and Iguazio have an extensive network of high-profile strategic partners, including AWS, Microsoft, Google, NVIDIA, Intel and MongoDB.
For more details on the partnership visit the Pure Storage website.
For a deeper dive into the solution read the technical blog.
About Iguazio
The Iguazio MLOps Platform enables enterprises to deploy and manage AI applications at scale. With Iguazio, enterprises can run AI models in real time, deploy them anywhere (multi-cloud, on-prem or edge), and bring to life their most ambitious AI-driven strategies. Enterprises spanning a wide range of verticals, including financial services, healthcare, manufacturing, entertainment, smart mobility and telecoms use Iguazio to automate MLOps and create business impact through a multitude of real-time use cases such as fraud prediction, predictive maintenance and real-time recommendations. Iguazio brings data science to life. Find out more on www.iguazio.com.
Source: Iguazio
