What happens when you stop thinking of satellites as data collectors and start thinking of them as data analysts? That is precisely the shift we explore in today's episode of Tech Talks Daily with Michael Bartholomeusz, CEO of NOVI.

Traditionally, Earth observation has relied on satellites to capture massive volumes of raw data, which is then transmitted back to Earth for processing. However, this model presents several significant challenges: cost, latency, and complexity. NOVI is flipping this model on its head. Instead of sending terabytes of data back down, their satellites analyze it in orbit and only transmit the results. That means smaller data packets, faster insights, and drastically reduced costs.

Michael and I dig into how NOVI's space-based edge computing infrastructure is opening new opportunities in defense, agriculture, mining, and more. With multiple sensors onboard each satellite and a proprietary AI processing platform, NOVI enables organizations to fuse and process Earth observation data in real time. It is a shift from intelligence as a feature to intelligence as the foundation.

We also discussed NOVI's evolving roadmap as it transitions from Department of Defense projects to a dual-use model that includes commercial services. Their commercial constellation is set to launch in early 2026 aboard SpaceX Transporter missions, and the company is already onboarding early adopters who are building custom inference models in preparation for this launch.

What stands out in this conversation is NOVI's goal of democratizing Earth observation. Their open-access platform enables users to retain full ownership of their data, marking a significant departure from the closed systems that currently dominate the industry. Lower cost, faster processing, and open access could change who benefits from space data and how.

So, what does it take to process AI in orbit? How do we reimagine satellites as part of the compute layer, not just the sensor layer? And what happens when access to real-time Earth intelligence becomes available to more than just governments and large enterprises? Listen in to find out.

Just two years ago, the launch of GPT-4 required the support of hundreds of experts, intensive computing power, and vast coordination. Today, that same process could be executed by a team of five. That is not an exaggeration. It is a signal of just how rapidly AI development is accelerating. In this episode of Tech Talks Daily, I’m joined by Gagan Tandon, Managing Director of AI & Data Services at TELUS Digital Solutions, to explore what is behind this extraordinary shift.

From the evolution of AI chip design to the efficiency gains from smarter algorithms and open-source tools, Gagan offers a clear and grounded look at how AI training has become more accessible and less resource-intensive. But the bigger question is, what can we do with that efficiency? For Gagan, the answer lies in impact. Whether it is addressing bottlenecks in global supply chains, enhancing diagnostics in healthcare, or reducing fraud in financial services, these advances in AI development are not just theoretical. They are opening new doors for innovation across industries.

We also explored how TELUS Digital Solutions supports enterprise transformation through its Fuel iX platform, which helps organisations transition from GenAI pilots to scalable, secure, ethical, and practical production systems. Gagan shared examples of how large-scale transformation can be approached with agility, especially when AI is aligned to specific business outcomes rather than simply layered on top of existing systems.

This conversation goes far beyond model training. It is about what's next in AI operationalization, what business leaders should prioritize when it comes to adoption, and how to avoid common pitfalls as technology continues to evolve faster than many are prepared for.

So how did we go from 300 engineers to five? What should enterprises be doing right now to take advantage of this momentum? And how can we make sure that efficiency does not come at the cost of responsibility? Join us as we explore the answers.

When I last spoke with Gaurav Kapoor five years ago, we were in the thick of a global pandemic. Remote work was still a novelty for many, AI was a distant concept for most businesses, and regulatory frameworks were trying to keep pace with the speed of technological change. Fast forward to today, and the conversation around AI and governance, risk, and compliance (GRC) has shifted dramatically. This made it the perfect time for a long-overdue catch-up.

In this episode, I welcomed back Gaurav, Vice Chairman and Co-founder of MetricStream, to discuss the changing face of GRC in an AI-driven world. AI has now reached a level of ubiquity that places it alongside electricity and Wi-Fi as a foundational layer of both business and everyday life. But with that integration comes risk, and with risk comes the need for smarter, more adaptive governance.

Gaurav shared how AI is no longer just about efficiency gains. It is becoming embedded into the fabric of enterprise risk frameworks, from real-time regulatory monitoring to predictive analytics and risk forecasting. We talked about the impact of the current political climate, including policy shifts following President Trump’s return to office and how deregulation narratives are colliding with the complexity of global compliance expectations.

This was not just a theoretical discussion. Gaurav broke down real-world use cases that show how large enterprises are navigating everything from redundant compliance testing to emerging threats discovered through AI-driven analysis. He also spoke candidly about the challenges ahead, how companies can fall behind if they wait too long to modernize their frameworks, and what is at stake when they fail to build trust into their AI systems.

So how do you evolve GRC in an age where the pace of change is relentless? What role does AI really play in risk leadership today? And how can companies move from reactive to proactive without losing control? Join me as we explore the next chapter of GRC with one of its leading voices.