What did we see at GTC? An AI community hungry for speed and simplicity

Our pilgrimage to the heart of AI 

Earlier this month, the Spectro Cloud team traveled to Washington, DC, for NVIDIA's GTC conference, arguably the year's most important event for the AI industry. The energy was high, fueled by major announcements around next-gen GPUs, networking, and data platforms, all of which support building powerful AI Factories through NVIDIA's AI Enterprise (NVAIE).

To state the obvious, NVIDIA and its hardware are at the literal heart of the AI revolution. Their releases this year reinforced just how fast the AI stack is evolving, and in so many different directions: from physical AI in robotics, to quantum computing and 6G networking. 

But for us the key concept that resonated across the show was the idea of scalable AI Factories. It shows how critical the infrastructure and the accompanying software stack around them have become for making AI real, both for practitioners and the platform teams that support them.

Even amid a government shutdown in the United States, the DC setting added urgency and perspective. It highlighted how essential secure, scalable AI systems are not only for commercial innovation but also for national security and defense, the public sector as a whole, and other regulated industries.

For us at Spectro Cloud, the event was doubly exciting as we officially launched our latest product: PaletteAI.

ICYMI: meet PaletteAI

PaletteAI is a software platform that helps companies quickly build and manage the infrastructure needed to run AI in production. If you missed the launch, here are three key things you need to know:

Speed for practitioners, control for platform teams.

PaletteAI platform solves a significant challenge for enterprises. As companies push to integrate AI into their infrastructure, platform teams focus on governance, security, and cost control. At the same time, AI and ML practitioners demand speed, flexibility, and access to the latest tools. This can sometimes create friction between the two teams that slows innovation and the path to ROI. 

PaletteAI unifies these needs into a single system. Platform teams create secure, reusable AI workload templates. AI practitioners then deploy them through self-service interfaces. This approach replaces fragmented workflows and manual infrastructure builds with reliable environments delivered in minutes.

Deep NVIDIA integration

PaletteAI gains significant strength from its deep integration with NVIDIA technologies and alignment with the AI Factory model. It runs on NVIDIA AI Enterprise and supports Blackwell GPUs, BlueField DPUs, and Spectrum-X networking. This integration allows enterprises to use validated infrastructure designs and software stacks from NVIDIA, as well as other open-source models and tools. 

A key enabler for AI factories

PaletteAI also helps organizations adopt the AI Factory concept by enabling modular, repeatable AI deployments across their environments without the usual operational chaos.

By combining PaletteAI with NVIDIA's stack, enterprises solve key AI operations problems. They eliminate idle hardware waste, speed up the path from experimentation to production, and maintain substantial compliance and governance. 

Platform teams design infrastructure with built-in controls. AI practitioners deploy with autonomy using approved templates. This model increases resource utilization, shortens time-to-value, and provides a secure, scalable foundation for enterprise AI. 

You can see why we were excited to get in front of real AI professionals at GTC to share the product and gather their thoughts.

So, what did we hear at GTC?

As expected, being on the GTC floor gave us a rare opportunity to speak with hundreds of practitioners, platform engineers, and technical leaders, and many of the interactions validated what we've been building.

At our booth and across the show, conversations revealed a deep hunger for solutions that simplify AI infrastructure without diluting control or security. I checked in with several of our SMEs who were in attendance and they had a lot of positive feedback to relay.

A much-needed AI productivity tool for real gains

Spectro Cloud’s Head of AI, Karl Cardenas, noticed how often attendees emphasized that Spectro Cloud is solving a real problem, not just promoting a shiny new abstraction. In a landscape full of hype, PaletteAI stood out for being grounded in practical utility. As Karl put it, "It was pointed out how we are actually tackling a real problem and not trying to convince the world that this is a solution that it needs."

One visitor told Karl, after learning about PaletteAI's self-service model, "You realize you have a productivity tool?" That comment stuck. PaletteAI isn't just about infrastructure. It's about enabling faster experimentation, faster iteration, and ultimately faster time-to-value for data scientists and AI teams. In short, the productivity gains are real.

A theme that kept surfacing was how refreshing it was that we don't fixate on Kubernetes despite our years of expertise. As Karl observed, "People appreciated that we don't focus on K8s. We see it as a means to an end." Our messaging reflects that, and it resonated strongly with attendees who are tired of wrestling with complexity for its own sake.

The ‘mindbending’ bridge between experimentation and production

Kevin Reeuwijk, our Principal Solution Architect, had similarly powerful takeaways. When speaking with platform engineers, Kevin found that our ability to stand up full-stack, AI-ready infrastructure from bare metal in just hours was "mindbending." 

These teams are used to projects taking months, if not years, and often limping forward with fragile, hand-built environments. Seeing PaletteAI stand up secure, enterprise-grade infrastructure in four hours was an eye-opener.

When Kevin spoke with data scientists or those supporting them, they zeroed in on PaletteAI's content-driven approach. The ability to build and deploy AI stacks including NVIDIA's NIMs and open source Hugging Face models, through shareable, reusable profiles had an immediate impact. Combined with PaletteAI Studio's stack profiles, it created an instant bridge between experimentation and production readiness.

The conversations also gave us a picture of some needs of the practitioners and platform teams. One recurring request was GPU utilization insights. Attendees were eager to know how efficiently their clusters were using GPU resources, for example, whether they had excess capacity or it was time to scale. This functionality is under active development for PaletteAI's GA release.

Turns out you can make everyone happy

Jon Bergfeld, Solutions Architect, echoed many of these themes. What struck him most was how PaletteAI speaks to both personas — platform engineers and data scientists. Platform teams loved the operational control and stability; data scientists appreciated the autonomy and speed. 

As Jon put it, "Simplifying platform teams ability to satisfy the requests of their users allows them to meet their goals.  And the scientists appreciate the self-service capabilities without having to wait for the platform teams to give them what they need." That alignment, he noted, validates PaletteAI's core design philosophy.

AI is for everyone

On a personal note, this was my first time representing Spectro Cloud at a significant event, and it was incredible to see how our team showed up. We had a constant stream of people stopping by from all walks of life: students, military personnel, government leaders, and commercial enterprise reps all of whom were thoroughly engaged with our team.

Everyone I spoke to was eager to learn more. Dozens of conversations, same themes: need for speed, security, and efficient AI infrastructure.

The AI revolution is well underway. And while tools, models, and platforms will continue to evolve, the core problem remains: how do we get AI into production efficiently, repeatably, and securely? Thankfully, Spectro Cloud is up to the task.

A history of AI innovation… yet the best is yet to come.

Spectro Cloud has spent years refining Kubernetes for real-world environments, especially at the edge. PaletteAI is the next step. 

It's not just another tool in the AI stack: it's a foundational system that helps organizations operationalize their AI toolchain across modern software and hardware, including the latest from NVIDIA.

PaletteAI will be generally available in early 2026. To learn more or request a demo, visit palette-ai.com.