SQream at NVIDIA GTC 2025: Cutting Through the AI Hype

There’s been a lot of noise lately about the “AI Factory.” NVIDIA’s CEO Jensen Huang lit up GTC 2025 with the idea that every business is becoming one – mass-producing intelligence using AI infrastructure. It’s a catchy metaphor. But buzzwords don’t build businesses. Outcomes do.

As the newly appointed CEO of SQream, I wanted to share a candid take – both on the AI Factory narrative and why I joined this company in the first place.

Why SQream? Why Now?

After two decades of leading tech companies through scale-ups, turnarounds, and global expansions, I’ve learned to spot the difference between hype and real potential. At SQream, I saw a team with deep tech, a strong vision, and a product that quietly solves one of the biggest problems in AI and big data: speed to insight at scale.

We’re not here to follow the latest buzz. We’re here to make AI actually work—for real businesses with real data challenges.

Making Sense of the AI Factory

The concept of an AI Factory isn’t wrong. But it’s often misunderstood. It’s not about adding a few LLM APIs and calling it transformation. It’s about turning raw, chaotic data into smart, timely decisions – at scale, reliably, and fast.

That only happens when you have:

• Infrastructure that scales without bottlenecks.
  
• Analytics that can keep pace with the business.
  
• Tools that don’t require an army of engineers to manage.

That’s where SQream fits in.

What We Showed at GTC 2025

At GTC, we weren’t just walking the expo floor – we were showing real, working tech:

• At Vultr’s booth, we demoed how SQream’s integration with NVIDIA GPUs and cloud-native architecture accelerates performance dramatically-processing massive datasets faster and cheaper.
  
• In a LinkedIn Live session, I broke down what the AI Factory really looks like when it’s not just slideware.
  
• In meetings with NVIDIA leadership and ecosystem players, we explored how to bring meaningful AI infrastructure to industries drowning in data.

The Real-World Use Cases We’re Focused On

Our customers aren’t building sci-fi futures. They’re:

• Manufacturing:
  Global manufacturers use SQream to implement AI-driven predictive maintenance and quality control. By analyzing sensor data across production lines in near real-time, they reduce downtime and optimize yield – turning massive operational data into smarter decisions.
• Telecommunications:
  One of the largest mobile carriers in Southeast Asia serves over 170 million customers across land and sea. But their network quality insights were trapped in siloed systems – too slow to act on. With SQream, they integrated disparate data sources into a unified, near real-time dashboard. That shift dramatically improved service visibility, slashed support response times, and enabled proactive network upgrades. The result? Higher customer satisfaction and reclaimed market share.
• Banking and Fintech:
  NCBA, a major East African banking group serving 60 million customers, struggled with slow analytics and fragmented data across business units. Their teams faced multi-day delays just to process and analyze data. After switching to SQream, query times dropped from hours to minutes, and data loading and prep time was cut by over 80%. Today, NCBA’s teams can make faster decisions, run more accurate customer behavior models, and innovate faster – while cutting costs and reducing infrastructure complexity.

 

These aren’t visionary slides – they’re use cases live in production, powered by SQream’s platform.

What’s Next

GTC 2025 showed us just how fast the landscape is shifting. At SQream, we’re doubling down on:

• Deeper integration with NVIDIA – bringing GPU-accelerated AI and analytics to the masses.
• Expanding our vertical-specific tools – so we’re not just general-purpose, but purpose-built for manufacturing, finance, telecom, and more.
• Continuing to simplify big data – so teams don’t need to trade speed for complexity.
  

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A Personal Note

Joining SQream wasn’t just a career move – it was a decision to bet on a team that gets it. I believe in this company’s mission, in the talent behind it, and in the impact we’re already making.

I’ve seen a lot of tech cycles. This one feels different – because for once, we’re not talking about potential. We’re talking about deployment. Impact. Real wins.

The AI Factory is here. We’re not just part of it – we’re building the infrastructure that makes it possible.

See you at GTC 2026.