In this episode, I’m joined by Michael Wu of Phison Electronics, recorded shortly after our meeting on the IT Press Tour in Silicon Valley. Michael takes us inside Phison’s latest breakthrough: the aiDAPTIV+ platform and its integration with StorONE’s ONEai solution. Together, they’re reshaping how enterprises think about AI training, inference, and data sovereignty.

Michael explains how aiDAPTIV+ acts as expansion memory for GPUs, reducing power consumption and cutting hardware costs by up to 10x. We also dig into the partnership with StorONE, which has produced a plug-and-play, storage-based AI solution that makes large language model training accessible to organizations of all sizes—including smaller businesses and universities that traditionally struggle with GPU access.

From the launch of the E28 Gen5 AI-enabled SSD controller to the endurance-driven Pascari X200Z SSDs, Michael shares the technical innovations under the hood and what they mean for performance and reliability. He also looks ahead to future workloads, where models with trillions of parameters will demand smarter, more scalable storage architectures.

If you’re an IT leader weighing the trade-offs between cloud-based AI and secure, on-premises solutions, or you’re simply curious about how storage is becoming central to AI acceleration, this conversation will give you a fresh perspective.

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How can organizations protect their most valuable asset, data, while unlocking its full potential through AI-driven insights? That is the question I explored on the IT Press Tour in Silicon Valley during a face-to-face conversation with Sanjay Poonen, President and CEO of Cohesity.

In this episode, Sanjay shares how Cohesity evolved from reinventing backup and recovery to leading the market in data security and cyber resilience. We discuss the game-changing acquisition of Veritas’s NetBackup business, the company’s growing footprint across healthcare, finance, government, and retail, and why uniting cultures and customers is key to their next chapter.

We dive into how Cohesity is using AI to transform backup data into a source of real-time intelligence, including its patented Retrieval Augmented Generation (RAG) capabilities developed in partnership with NVIDIA. Sanjay also explains how this innovation is enabling businesses to meet strict data sovereignty requirements while benefiting from cloud agility.

From cyberattack recovery and on-premises innovation to working with some of the biggest names in AI and cloud, Sanjay offers a candid look at leadership in a time of rapid growth. If you want to understand how AI and cybersecurity are converging to shape the future of enterprise data, this conversation delivers practical insight, strategic thinking, and a clear vision for what is ahead.

In this episode of Infrastructure as a Conversation, I’m joined by Tommi Kannisto, founder of Storadera, a cloud storage company based in Estonia that’s quietly building a smarter, simpler alternative to hyperscalers like AWS.

We dive into how Storadera has engineered its own storage software from scratch to deliver secure, S3-compatible cloud storage with a unique hyper-converged architecture. It’s all about cutting unnecessary hardware, avoiding bottlenecks, and delivering transparent pricing that makes sense to growing businesses.

Tommi explains:

• How Storadera’s hyper-converged design replaces gateways and load balancers with lean software
• Why performance with small files became a key differentiator
• What makes their multi-tenant system attractive to retail partners
• The impact of data sovereignty concerns on customer growth across Europe
• Why Canada is now looking eastward, not southward, for storage partners
• The Estonian tech culture that helped birth 10 unicorns from a country of just 1.3 million

We also talk about the cultural mindset that powers Estonia’s startup scene, from engineers cold-messaging CEOs for advice to a national infrastructure designed for digital innovation. Tommi shares Storadera’s future roadmap, including plans to use AI to optimize disk read and delete operations without raising prices.

If you’re curious about what comes after hyperscale, why storage software still matters, or what makes Estonia such a hotbed for digital infrastructure innovation, this is an episode you’ll want to hear.

🔗 Learn more at storadera.com 📍 Want Storadera in your country? Join their regional waitlist on the website.

What if running databases in Kubernetes could be as simple as spinning up a container—without cloud lock-in or complexity?

In this episode of IT Infrastructure as a Conversation, I’m joined by Tamal Saha, founder of AppsCode, a company rethinking how we manage data on Kubernetes. We met during the IT Press Tour in London, and this conversation dives deep into how AppsCode is tackling one of the most stubborn challenges in enterprise IT: stateful workloads.

From CubeDB to Stash, Voyager, and KubeVault, Tamal walks us through the full story—from his early days at Google and the emergence of Kubernetes to bootstrapping a company through open source tools and evolving it into a full-fledged enterprise platform. We explore:

• The challenges of running databases in Kubernetes and why traditional VM-based infrastructure falls short
• Why database provisioning, backups, secret management, and ingress need Kubernetes-native solutions
• How AppsCode pivoted from open source tools to a sustainable business model
• Real-world enterprise use cases—including a major European telco’s cloud-native transformation
• The road ahead: vector databases, open telemetry, and AI-driven automation

If you're a platform engineer, DevOps leader, or just curious about where Kubernetes is headed next, this conversation offers rare insights into building data platforms from the ground up, with a practical, product-led mindset.

So tune in to hear how one founder turned a container-native vision into a global business that’s helping companies modernize data operations without losing control.

In this episode of IT Infrastructure as a Conversation, I sit down with Thomas Bak, CEO of Auwau, fresh from our meeting at the IT Press Tour. We explore how his journey from running a managed service provider to founding Auwau led to the creation of CloudTility — a self-service, multi-tenant portal built for modern data protection and storage needs.

Thomas unpacks how CloudTility helps MSPs and enterprises unify control across vendors like IBM, Rubrik, Cohesity, and more. He explains why customers are leaning toward on-premise deployment to maintain control and meet compliance demands, and how the platform supports complex organizational structures with flexible role-based hierarchies and automated billing.

We also cover how CloudTility empowers IT teams to act more like internal MSPs, reduces reliance on spreadsheets, and enables partners to white-label services with minimal overhead. Whether you’re managing backups across regions or looking to scale your services, Thomas shares practical insights into solving real infrastructure challenges with clarity and control.

On this episode of IT Infrastructure as a Conversation, I explore a fresh approach to one of the oldest headaches in enterprise IT: migrating legacy databases without breaking everything.

My guest is Jacek Migdał, co-founder and CEO of Quesma, a startup tackling the messy reality of old data stacks, rigid licensing, and costly, high-risk migration projects. Jacek shares how Quesma’s database gateway acts as a smart proxy, allowing companies to switch data stacks gradually, test changes safely, and avoid the dreaded “big bang” migration that so often fails.

We unpack how Quesma blends pragmatic engineering with AI-driven automation, from SQL extensions that enrich data inside the database to “smart charts” that generate meaningful visualizations without complex BI tools. Jacek also explains why even modern industries like telecom and travel still wrestle with legacy systems and how a flexible, proxy-based approach keeps critical operations online while modernising behind the scenes.

If your team is wrestling with outdated data infrastructure but cannot afford downtime, you will want to hear how Quesma turns risky transitions into manageable, incremental improvements.

This is a candid look at the reality behind today’s data stack promises and a reminder that when it comes to enterprise infrastructure, practical steps often beat grand plans.

In this episode of IT Infrastructure as a Conversation, recorded live at the IT Press Tour, I caught up with Raju Datla, CEO of Fabrix.ai, to talk about a shift that could redefine how IT operations are managed. Formerly known as CloudFabrix, the company has evolved with a sharper focus on what it calls agentic AI: technology that works alongside humans to make smart, controlled decisions at scale.

Raju’s story begins at the Indian Institute of Technology and winds through Silicon Valley, where he has founded several ventures grounded in solving real-world tech problems.

Reducing Noise, Increasing Value

One of the standout achievements we discussed is Fabrix.ai’s ability to reduce alert noise by up to 95 percent. In large environments with millions of daily notifications, that kind of reduction changes how teams work. Instead of chasing false alarms, IT professionals can focus on what matters: stability, uptime, and real outcomes for the business.

The platform does this through a layered architecture Raju describes as the three fabrics: data, AI, and automation. Each plays a role in bringing clarity and action to complex infrastructure environments. Data is unified from dozens of sources. AI makes decisions based on context. Automation executes those decisions while keeping humans involved in key steps.

Strategic Moves and Trusted Partners

Fabrix.ai has not gone it alone. Through close relationships with Cisco, IBM, and Splunk, the company has stayed connected to both market demand and enterprise pain points. These partnerships are not just logos on a slide. They are part of how the platform has been built to handle real-world complexity.

And the results are tangible. Whether it is automating resolution, tracking full alert lifecycles, or offering visual storyboards for better decision-making, Fabrix.ai is helping enterprise teams keep up with a pace of change that is not slowing down.

Agentic AI in Practice

The concept of agentic AI comes up often in this conversation, and for good reason. Unlike systems that simply follow rules or surface alerts, this approach blends autonomy with awareness. It does not just generate insights; it acts on them. And it does so in ways that respect the role of human judgment.

Raju explains that this is not about removing people from the loop. It is about giving them systems that can scale, adapt, and support smart decisions. In that sense, Fabrix.ai is not replacing IT teams. It is extending what they can do.

For leaders wrestling with fragmented tools, alert fatigue, and growing complexity, this episode offers a fresh perspective and a reminder that practical, scalable AI is already here.

Raju’s parting advice to entrepreneurs and IT leaders alike? Solve the problems you care about. Passion always carries more weight than a quick exit plan.

Listen in to learn how Fabrix.ai is helping enterprises bring order to operational chaos, one intelligent decision at a time.

Is AI Infrastructure Broken? A Candid Conversation with Volumez

AI adoption is accelerating, but most enterprises are still stuck in the pilot phase. Cloud costs keep climbing, GPUs go underutilized, and data pipelines struggle to keep pace. If AI is the future, why is the infrastructure built to support it so often stuck in the past?

In this episode, recorded live in Silicon Valley during the IT Press Tour, I sit down with John Blumenthal, Chief Product Officer at Volumez, and Diane Gonzalez, Senior Director of Business Development and Product. Together, we unpack what is really holding AI back and explore how Data Infrastructure as a Service (DIaaS) could change the equation.

We explore:

• Why traditional AI infrastructure models are inefficient and unsustainable
• How DIaaS enables just-in-time, automated infrastructure tuned to each workload
• The role of GPU and data scientist efficiency in determining AI ROI
• How Volumez achieved industry-leading results in the MLCommons benchmark
• Why hybrid and multicloud strategies demand a fundamentally different infrastructure approach

John and Diane share firsthand insights from working at the intersection of data, cloud, and AI infrastructure. They argue that achieving meaningful return on AI investment requires more than hardware upgrades or clever provisioning. It means embracing automation, profiling cloud capabilities in real time, and architecting pipelines that adapt to the specific demands of each phase in AI and ML workflows.

Whether you're building AI platforms, running data science teams, or managing cloud infrastructure, this conversation offers a grounded look at how to make AI actually scalable.

Are you wasting your most valuable resources or are you ready to run AI workloads at full speed with none of the bloat?