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If your team is wrestling with outdated data infrastructure but cannot afford downtime, you will want to hear how Quesma turns risky transitions into manageable, incremental improvements.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

Behind every seamless digital experience is an infrastructure team working hard to keep systems scalable, responsive, and resilient. In this episode of IT Infrastructure as a Conversation, I’m joined by Jesmar Cannaò, COO of ProxySQL on the IT Press Tour,

We explore the story behind one of the most trusted open source tools in database management today.

What began as a side project born from the frustrations of a single DBA has evolved into a critical component for teams managing MySQL and PostgreSQL environments around the world. Jesmar walks us through the origins of ProxySQL and explains how it empowers DBAs by placing intelligent query routing, load balancing, and failover handling directly in their hands.

We discuss the architectural advantages of ProxySQL in both cloud-native and on-premise setups, its ability to operate with minimal friction inside Kubernetes, and why open source remains at the heart of its mission. Jesmar also offers a candid look at what it takes to build a distributed team, maintain performance across time zones, and foster a global community of contributors and users.

As database architectures grow more complex and DBA roles continue to shift, ProxySQL is evolving to meet those changes head-on. With the recent alpha release of its PostgreSQL protocol support and plans to expand further in 2025, Jesmar outlines how the team is staying ahead of industry demand.

Whether you're a database engineer, a cloud architect, or simply someone trying to future-proof your infrastructure, this conversation is full of practical insight into what open source can offer in a fast-changing world.

Explore more at proxysql.com and join the conversation around high-performance infrastructure that does not compromise on transparency, flexibility, or control.

In a world where business users expect instant insights from tools like Power BI and Tableau, few stop to consider the heavy lifting happening behind the scenes. Dashboards may look simple, but the infrastructure powering them often involves layers of complex data engineering, expensive queries, and frustrating delays. This mismatch is what Nicolas Korchia, Co-founder and CEO of Indexima, calls the BI paradox.

In this episode of IT Infrastructure as a Conversation, Nicolas joins Neil to explore how Indexima is solving this issue by automating the most painful parts of business intelligence. Rather than forcing engineers to build yet another manual data pipeline, Indexima uses AI to identify query patterns and automatically generate dynamic tables directly within Snowflake. The outcome is faster dashboards, lower compute costs, and a smoother experience for analysts and engineers alike.

We unpack how Indexima’s engine monitors live dashboard usage, detects inefficiencies, and rewrites queries on the fly to target optimized aggregation layers. This not only improves performance but also contributes to sustainability by reducing the volume of data scanned and processed. For organizations under pressure to balance data speed with environmental impact, it is a practical and forward-looking approach.

Nicolas also shares real-world use cases from retail and finance, where customers have slashed dashboard load times from minutes to milliseconds and eliminated the need for nightly data extracts. The conversation touches on broader trends too, including the role of large language models in BI workflows and how tools like ChatGPT might soon assist in building semantic layers.

For anyone responsible for scaling data infrastructure, this episode provides a grounded look at how automation is reshaping BI from the ground up. If your teams are still wrestling with slow dashboards and spiraling query costs, this is a conversation worth listening to.

What if the future of analytics was not about working harder, but about letting your infrastructure work smarter?

As AI agents begin to influence how businesses operate, there's growing urgency around building infrastructure that supports their complexity without adding new risks. In this episode of IT Infrastructure as a Conversation, I speak with Alexander Alten, Co-Founder and CEO of Scalytics, about the architecture powering the next generation of AI and machine learning systems.

Alexander’s journey includes leadership roles at Cloudera, Allianz, and Healthgrades, and a deep commitment to building scalable, privacy-respecting technologies. At Scalytics, he's helping organizations avoid the limitations of centralizing data by building distributed systems that support federated learning. Rather than extracting and duplicating data across systems, Scalytics enables analysis directly at the source, making it easier for businesses in regulated industries to innovate with confidence.

Recorded live at the IT Press Tour in Malta, our conversation dives into the origins of Scalytics Connect, the company's AI agent infrastructure that leverages open-source frameworks like Apache Wayang. We explore why ETL pipelines often create fragility instead of flexibility, how decentralization supports both compliance and collaboration, and why open-source technologies continue to outperform closed systems over the long term.

For any CIO, CTO, or data architect looking to align AI capabilities with real-world constraints, Alexander’s perspective offers a refreshingly pragmatic path forward. His framework simplifies the complexity of federated machine learning while preserving data sovereignty, auditability, and future-proof flexibility.

If your organization is struggling with data silos, regulatory friction, or the scaling of AI models, this episode offers insight into a model that avoids duplication, improves trust, and accelerates results by treating infrastructure as the foundation for intelligent systems.

Could sustainable IT hold the answers to rising infrastructure costs and environmental pressure?

In this episode, recorded live during the IT Press Tour in Malta, we speak with François Machacek, an IT veteran with nearly thirty years of experience and a strong focus on digital sustainability. Now part of the team at EasyVirt, François is helping organizations measure and reduce the environmental impact of their digital operations.

The conversation begins with François’s career journey, from managing enterprise data centers across Europe to becoming a leader in responsible IT. He introduces EasyVirt’s technology, which includes DCscope, DCnetscope, and CO2scope, and explains how these tools provide real-time, high-frequency resource usage measurements across virtualized and hybrid environments. This level of visibility helps organizations make informed decisions that improve efficiency and reduce carbon emissions without compromising performance or security.

We examine how the environmental costs of digital technology are growing fast, especially with the expansion of AI workloads and data center demand. François discusses how EasyVirt addresses this challenge by offering software that works inside client environments, avoids reliance on average estimates, and instead delivers precise, continuous monitoring. He outlines the financial and environmental benefits clients are seeing in both the short and long term, including reduced compute waste, time savings in planning, and improved reporting against ESG targets.

The episode also highlights how FinOps and GreenOps can work together to guide smarter infrastructure use. François explains how these principles allow IT teams to balance financial planning with environmental goals, resulting in better resource control, improved compliance readiness, and more credible emissions reporting.

Looking ahead, François shares what’s next for EasyVirt, including new tools for measuring AI energy use, upcoming multi-impact assessments (carbon, water, materials), and a free new comparison platform called ECLIO. This tool gives IT teams insights into pricing and emissions data across major cloud providers, supporting better planning for cloud migrations.

If your infrastructure strategy needs to align with both cost efficiency and sustainability expectations, this episode provides a grounded look at how to get there using accurate data and practical solutions.

What does long-term data preservation really require in a digital-first world where technology changes faster than it can be archived? In this episode of IT Infrastructure as a Conversation, recorded during the IT Press Tour in Malta, we explore a fresh perspective with Antoine Simkine, co-founder of DigiFilm Corporation.

Antoine’s background is nothing short of extraordinary. Having produced digital visual effects for iconic films like Amelie, Alien Resurrection, and The Ninth Gate, and serving as VFX producer for 20th Century Fox’s I, Robot, Antoine understands the challenges of preserving digital assets in an industry where formats evolve and decay at a relentless pace.

Bringing this cinematic experience into the world of infrastructure, Antoine shares how the fragility of digital media inspired him to rethink data preservation. We examine his journey from pioneering digital VFX to founding DigiFilm Corporation and developing Archifix, a solution that combines the permanence of film with the precision of digital encoding.

As organizations generate more data than ever before—and as regulatory demands for data integrity and security intensify—this conversation shines a light on why traditional storage methods may not be enough. Antoine explains how Digifilm’s approach addresses the risks of obsolescence, media degradation, and escalating costs associated with perpetual migration.

Beyond cinema, Antoine reveals how sectors such as defense, nuclear energy, and architecture are beginning to recognize the need for offline, futureproof data storage strategies. Could an idea rooted in the oldest form of recording still hold the answer to our most modern infrastructure challenges?

What steps should enterprises take today if they want their critical digital assets to survive for centuries? And how can organizations balance innovation with the responsibility of long-term stewardship?

This is your conversation.

Learn more at https://digifilm-corp.com/home