In this episode of Bright Founders Talk, we sit down with Jorge Palomar Giner, the Co-Founder and CEO of Galtea, a company at the forefront of AI validation. With a background in computer engineering and a career rooted in high-performance computing at the Barcelona Supercomputing Center, Jorge brings deep technical expertise to the table. 

Galtea was born out of firsthand experience with the challenges of deploying large language models in production environments. The company now offers a robust quality assurance stack, helping organizations validate AI systems with a data-first approach. Jorge shares how curiosity and a desire for lasting impact have shaped his journey from engineer to entrepreneur. 

He also reflects on the stark contrast between coding in a technical bubble and navigating the complexities of leading a startup. In this candid conversation, Jorge opens up about the beauty and the difficulty of founding a company in such a transformative space. Join us as we explore his inspiring path and Galtea’s mission to make AI systems more reliable for the real world.

From Code to CEO: Jorge’s Leap from Supercomputers to Startups

When Jorge Palomar Giner talks about the early days of Galtea, it doesn’t sound like a flashy Silicon Valley origin story—it sounds like two brilliant minds stumbling into a real-world problem and deciding to fix it. Jorge and his co-founder met at the Barcelona Supercomputing Center, where they were knee-deep in training large language models before most of the world even knew what "LLMs" stood for. The challenge? Making these models actually reliable in production. “We struggled and experienced firsthand all the problems around the reliability of those models,” Jorge recalls. So they built a quality assurance stack—first as an internal tool, then as the foundation for what would become Galtea.

What started as a project born out of necessity soon turned into a mission: helping developers everywhere test AI with context-aware, high-quality data. Galtea now supports organizations in validating AI solutions with a “data-first” approach, and Jorge’s journey from engineer to CEO is anything but traditional. He didn’t set out to be a founder—he just followed his curiosity. “I always try to do things that, when I’m old, I’ll remember,” he says with a smile. That mindset led him from coding to company-building, and eventually into the world of selling a product he once built for himself.

But stepping into the CEO role brought a whole new set of challenges. “As an engineer, you live in a bubble,” Jorge says. “Then suddenly you’re out there selling, pitching, adapting your mindset—it’s crazy.” He didn’t just have to learn new skills; he had to see the world from a completely different angle. Going from building systems to building a business meant facing rejection, making hard decisions, and navigating uncertainty—every single day. And while Jorge admits he's still learning, it’s clear that his blend of technical depth and human curiosity is exactly what makes Galtea’s story worth telling.

From Sports Fields to Sales Funnels: How Jorge's Competitive Spirit Drives Galtea’s Growth

Jorge didn’t just wake up one day and decide to be a founder—his mindset was shaped long before Galtea came to life. A lifelong athlete, he's used to pushing limits and chasing goals, and that competitive streak didn’t fade when he stepped off the field. “Being active in sports helped me stay ambitious and hardworking,” he says. That same drive shows up in how he tackles business: set a goal, work hard, push forward. His technical background as a computer engineer also gave him a powerful edge—not just in building a product, but in approaching every business challenge like a puzzle to be solved.

Interestingly, Jorge sees his engineering mindset as a secret weapon for leadership. Sure, being a CEO requires big-picture thinking, but that doesn’t mean leaving the details behind. He talks about applying structured, data-driven thinking even to areas like sales or operations. “You start to measure everything,” Jorge explains. It’s not about obsessing over every stat—but when the time is right, having that precision makes scaling smoother. It’s this blend of detail-oriented focus and strategic awareness that helps him keep Galtea both grounded and growing.

When introducing Galtea to a new organization, Jorge keeps things simple—but strategic. His team always starts by talking directly to developers, because they’re the ones who’ll use the product. The first step? Understand the problem. Are they investing in Gen AI but stuck at the validation stage? If the answer is yes, it’s game on. Jorge believes the product speaks for itself—once teams see it in action, they get it. But he admits the toughest part is actually getting in front of the right people. “The bottleneck is scheduling that first discovery call,” he says. To solve that, they’re testing everything from outbound tactics to building community—and just like in sports, Jorge knows the win is in playing the long game.

The AI Hype Trap: Why Most Enterprise AI Projects Fail—And What Jorge Thinks Can Save Them

By the time Jorge Palomar Giner steps into a conversation with a potential client, he’s already seen the pattern. A CEO declares, “We must adopt AI!”—and suddenly, every department from sales to procurement is pitching their use case. That rush creates internal AI teams scrambling to bring projects to life, all while being held to the impossible metric of “time to production.” The catch? Most of these initiatives never actually make it there. “95% of enterprise POCs fail,” Jorge says. “They can’t build enough trust to get real users or support mission-critical tasks.” And that’s where Galtea steps in—not to promise AI magic, but to bring evidence, clarity, and a way forward that actually works.

Still, Jorge is the first to admit: things are changing fast. He’s seen the shift from blind optimism to cautious pragmatism, with companies beginning to understand the very real limitations of current AI tools. But that doesn’t mean we’re standing still. “Every six months, these models take a leap,” Jorge explains. One moment, it’s just text prediction—next thing you know, AI is solving math problems and writing solid code. He’s seen first-hand how far we’ve come, and while the limitations today are real, tomorrow’s breakthroughs are already in motion. For companies navigating this space, that means staying sharp, realistic, and future-ready.

And despite the hurdles, Jorge is fired up about what’s ahead—especially when it comes to reasoning models. These advanced systems don’t just spit out answers—they plan, adapt, and solve problems in surprisingly human ways. “It’s incredible what these models can do without being programmed for it,” he says. The possibilities stretch across industries, but it’s the impact on research that excites him most: from healthcare to physics, he believes AI could accelerate discovery in ways we've never seen before. “If we get this right,” he adds, “we’re not just improving business—we’re advancing humanity.”

Why Error Sensitivity Is the Real Battleground for AI—and Jorge’s Betting on It

Ask Jorge which industries benefit most from Galtea’s solution, and he doesn’t hesitate. It’s not about market size or trendiness—it’s about error sensitivity. “You can afford mistakes in some tools, but not when you’re paying salaries or diagnosing patients,” he says. That’s why industries like finance, healthcare, insurance, legal, and HR are top of Galtea’s client list. For these sectors, even the smallest AI misstep can cause real damage. And as AI agents replace traditional UIs with natural language interfaces, Jorge sees a future where AI quality assurance becomes as standard as software testing is today.

Of course, building trust in AI doesn’t happen overnight. Jorge encounters a spectrum—some companies are cautious, others overly ambitious. The good news? Organizations are becoming more realistic about what GenAI can (and can’t) do. But still, he sees some teams forcing AI into problems it just isn’t ready to solve. “Sometimes you already know it won’t work in the short term,” he says, shrugging. He’s not against ambition—he just believes in backing it up with evidence and ethics. In areas like immigration, health, or law, Jorge is firm: AI should support decision-making, not replace it entirely.

As the interview wraps, Jorge leaves future founders with a clear, no-nonsense message. If you’re waiting for the perfect time to start your startup, don’t. It won’t come. “You’ll never be ready enough,” he says. “If you're convinced your idea can work, then the best moment to build is now.” That mindset—decisive, curious, and grounded in action—sums up Jorge’s journey. From engineering supercomputers to building AI validation for high-stakes industries, he’s not just predicting the future. He’s helping build it, with quality and trust at the core.