Data Orchestration: Data that moves as fast as AI

by Gavin Sutton, Head of Marketing

So much potential, yet so many silos. AI is being adopted at a rapid rate, with businesses investing in high-performance compute, multi-GPU servers, and scalable storage. However, there’s a problem. Data is stuck in silos, limiting the business impact from AI. Many assume that more GPUs or faster storage will solve the challenge, but it’s not the hardware that’s the problem, it’s the inability to access and move data across environments. In this blog we look at how data orchestration can unlock your customers’ AI infrastructure.

The Data Dilemma

One thing is for sure, as AI models grow in complexity and size, so does the volume of data they require.  Where this data is stored is often where the issues arise. It’s stored on local NVMe drives in GPU servers, in network-attached storage (NAS) systems, on tape archives and in the cloud.  Each of these repositories is effective in isolation, but without intelligent data orchestration between them, performance slows, agility suffers, and costs spiral.  This disconnect is especially painful for customers running hybrid or multi-cloud environments, where manually shifting data between on-prem systems and the cloud becomes time-consuming and operationally expensive. This is why customers need to rethink their data layer.

What Is Data Orchestration?

Rather than treating each storage tier as a separate entity, data orchestration is a mechanism that creates a unified, policy-driven data layer that spans the edge, core, and cloud. This allows customers to automate how data is placed, moved, and accessed. In the AI era, this means that AI workloads can always interact with the right data at the right time, regardless of where it physically resides. 35% of companies view data management as a more significant inhibitor to scaling AI workloads than computing resources¹ because legacy data architectures do not meet the demand for modern AI.

Activating Underused NVMe with Tier 0

Today, vast amounts of NVMe storage already exist inside many GPU servers, but much of it remains siloed and underutilised. Data orchestration changes this by turning local NVMe into shared, ultra-high-speed Tier 0 storage. Tier 0 refers to the fastest and most responsive tier of storage, typically reserved for mission-critical workloads. In the context of AI, it plays a vital role in accelerating training, inferencing, and real-time content generation. It eliminates data limitations and maximises GPU utilisation. Instead of deploying complex external storage systems, orchestration unlocks high-performance, low-latency capacity in hours, using the infrastructure customers already own.

Enabling Hybrid Cloud AI Workflows

Data orchestration solutions ensure that GPUs are no longer left idle waiting for data. Developers spend less time managing pipelines and more time extracting insights. Storage costs decline, and performance improves. More importantly, orchestration opens the door to true hybrid cloud flexibility. AI workflows can seamlessly scale between on-prem and cloud environments without disruption, all while maintaining compliance, governance, and security. This capability is particularly critical as AI models move from the development into production, where agility, predictability, and automation are essential for real-world success.

Conclusion

Having the right data infrastructure in place is one thing, but if your customers cannot orchestrate their data, they’re likely not leveraging its true potential. As AI use cases continue to expand, the need to unify and automate data movement across environments has never been greater. At Titan, we’ll help you design and build an AI-ready infrastructure for your customer, optimised with leading data orchestration technology that unifies their unstructured data across sites, clouds, and any storage. Eliminate silos, maximise performance, and enable true hybrid AI workflows. In the era of AI, data orchestration is essential.

Contact sales to learn more about our data orchestration options.

¹ S&P Global Market Intelligence, Discovery Report “Global Trends in AI,” August 2024