MinIO and PwC Announce Joint Business Relationship

MinIO has announced a joint business relationship with PwC Canada to build, co-sell, and co-market cloud-based AI and ML solutions to Canadian enterprises across various industries.

MinIO is known for its Kubernetes-native, software-defined S3 compatible object store that comes standard with Kubeflow, TensorFlow, and H20.ai. As a popular object store for machine learning, analytics applications, databases, and web applications, MinIO says its object store has a simple and scalable architecture that can be deployed on public clouds, private clouds, Kubernetes distributions, and the edge. The company notes its object store has been starred on Github over 35,000 times and has over 979.5 million Docker pulls.

The lead PwC partner in the relationship is Vik Pant, PwC’s partner of its data and analytics practice. Pant is a researcher and practitioner of conceptual modeling and applied AI who MinIO says has built a pre-eminent AI and ML practice in Canada.

“For our clients, acquiring the knowledge most important to their operations, securing that information and using it optimally are critical – now more than ever before,” said Pant.

The companies announced their partnership will focus on the democratization of data through AI and ML applications and that they aspire to deliver a unified semantic layer through which applications, enterprise users, and processes can interoperate with all decentralized, distributed, federated, and heterogeneous data.

“This offers joint customers a reset button by allowing them to break down the barriers that exist between clouds — public, private, and edge,” MinIO said in a release. “Elements such as governance, monitoring, compliance, and oversight must also be architected in — intentionally and thoughtfully as responsible and beneficial AI is deployed in the enterprise.”

MinIO acknowledges that creating a completely unified multi-cloud platform is a tall order but says the analytics modernization space is a good starting point: “In the race to be a knowledge enterprise, inevitably there is database, datastore, and reporting balkanization. This is suboptimal on multiple levels. Together, PwC and MinIO are positioned to tackle this problem from an expertise perspective, from a performance perspective, and from a scale perspective.”

“PwC’s engagements combine services, product, and software to solve AI/ML problems at scale. The PwC team has a deep understanding of how to turn raw bits, blobs or objects into something meaningful for the bottom line or top line,” said Kris Inapurapu, chief business officer of MinIO. “The ability to create a multi-cloud data infrastructure from edge to core is a unique capability of MinIO’s, and will inform the relationship with PwC Canada going forward as the enterprise becomes more automated yet retains an ethical footing.”

News of this partnership comes on the heels of an earlier MinIO announcement of its deepened strategic partnership with Intel. The company says its object store is optimized for Intel’s 3rd-generation Xeon processors at a granular level and includes built-in Intel AVX-512 single instruction multiple data (SIMD) acceleration capabilities.

“Every enterprise today is a data enterprise, and every enterprise today needs mature multi-cloud experiences. Intel sees this across our portfolio and is excited to work with MinIO to address the need in this environment,” said Arijit Bandyopadhyay, CTO, enterprise analytics and AI, and head of strategy, enterprise and cloud group at Intel Corporation. “We’re bullish about our collaboration with MinIO because performance at scale is critical for AI and Augmented Analytics workloads. MinIO, with its software-defined, high performant S3 object storage optimized for 3rd Gen Intel Xeon Scalable processors, helps enterprises overcome challenges of large primary storage across a range of use cases from Kubernetes-powered cloud applications to AI/ML/advanced analytics workloads.”

MinIO was valued at $1 billion as of a $103 million Series B round this past January.

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