Canada’s artificial intelligence (AI) and machine learning (ML) credentials are well known to those in the space. Some would argue that Toronto, not Silicon Valley, is the center of the western AI universe. Diplomatically sidestepping that debate, there is no doubt that there are big things going on north of the border.
That is why we are so excited to announce our relationship with PricewaterhouseCoopers Canada on AI/ML work. Together the two organizations will build, co-sell, and co-market cloud-based AI and ML solutions across industries from Vancouver to Saint John.
The relationship is broad and will cover public clouds, private clouds, Kubernetes distributions, and the edge. Multi-cloud will be a large part of the work we do together, which makes sense as every enterprise is a multi-cloud enterprise at this point. The relationship will cover everything from pre-packaged solutions to bespoke engagements.
The key, however, is that this is a true best of breed partnership.
Vik Pant, the lead PwC partner in the relationship, has built the pre-eminent AI/ML practice in Canada. PwC’s engagements combine services, product, and software to solve AI/ML problems at scale. His team has a deep understanding of how to turn raw bits or blobs or objects into something meaningful for the bottom line or top line.
MinIO is the standard for AI/ML storage. Software-defined, S3 compatible and hyper-performant — MinIO comes standard in things like Kubeflow and is plugged into every major software stack from TensorFlow to H20.ai.
Together, the companies will be focused on the democratization of data through AI/ML applications. This can and will take many forms over the next few years, but at its core all enterprises are data enterprises and no enterprise is an autonomous enterprise. There are users of data, there are consumers of data, there are stewards of data and there are decisions that are made off data — and most of those decisions are made by humans.
Enterprises generally start with the right goals and strategy, but the dynamic nature of competition ensures that the playing field is always shifting. Add to that technology choices that are made upstream and are constantly evolving and the enterprise ends up with restricted flexibility to make good on the mission of democratizing data.
Together, MinIO and PwC believe they can offer a reset button to their clients by allowing them to break down the barriers that exist between clouds — public, private, and edge.
We noted that every enterprise is a data enterprise, but every enterprise is also a multi-cloud enterprise. Whether by design, M&A, or shadow IT, enterprises have data on disparate clouds. Together, MinIO and PwC aspire to deliver a unified semantic layer through which all applications, all users in the enterprise, all processes in the enterprise, can seamlessly, frictionlessly, and transparently interoperate with all of the decentralized, distributed, federated, heterogeneous data.
That is a tall challenge and will not be solved overnight — however, the two companies have a starting point: the analytics modernization space. 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.
While much of that work will be custom, there will be pre-built industry-specific applications that emerge too — and through the power of Kubernetes and MinIO, those applications will be able to run anywhere the enterprise wants them to. Over time, those PwC-built applications will replace the ultra-complex spaghetti diagram integrations between all of the enterprise’s process engines and all of the different data systems that those process engines touch.
We are very excited at the prospect of this work.
One additional element worth noting is that PwC has built a strong leadership position around ethical AI. This is less about HAL9000 and more about the principles around transparency, interpretability, explainability, fairness, biasing, and privacy. Elements such as governance, monitoring, compliance, and oversight must be architected in — intentionally and thoughtfully as responsible and beneficial AI is deployed in the enterprise.
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.
We will be producing more content here in the coming weeks as we build solutions together and advance the state of art in the space. If you want to reach out, drop us a line at firstname.lastname@example.org and we can talk about what we might accomplish together.