3264: How Deepdub Is Scaling Storytelling Without Losing the Human Touch

What if AI could help your content speak every language without losing its heart? In today’s episode, I sat down with Oz Krakowski, Chief Business Development Officer at Deepdub, a company reshaping how stories cross linguistic and cultural borders through AI-powered dubbing. As global demand for diverse entertainment continues to surge, Deepdub is offering studios a new way forward—one that balances scale with emotional fidelity. Oz walked me through how Deepdub’s platform enables post-production teams to dub content into over 130 languages and dialects, with output that respects the tone and intent of the original performance. This isn’t about replacing human creativity—it’s about integrating it into smarter workflows. Through a hybrid approach, Deepdub fuses cutting-edge AI with seasoned voice actors, directors, and editors to maintain authenticity while massively improving efficiency. From monetizing dormant titles trapped in single-language formats to opening up live broadcasts for real-time localization, the implications are wide-ranging. Oz also shared how Deepdub Live is already unlocking access to new global audiences for sports, conferences, and beyond—potentially transforming how we experience real-time events. We also explored the deeper economics of AI dubbing, especially as the cost of localization begins to fall, making it more viable to bring overlooked content into untapped markets. Whether it’s delivering content in regional dialects or enabling personalized voice experiences across industries like eLearning and customer service, the roadmap for AI localization is expanding far beyond the entertainment world. At a time when studios are re-evaluating their content strategies, Deepdub offers a glimpse of what's possible when AI meets cultural intelligence. Could your next global audience already be waiting? Have you considered how AI might help your content reach new viewers without losing its original voice?

How do you uncover misinformation and financial fraud hidden in plain sight across thousands of digital platforms during a global election cycle? In this episode, I spoke with Jim Webber, Chief Scientist at Neo4j, to explore how graph database technology is being used to expose coordinated disinformation campaigns, empower AI systems, and help enterprises manage the complexity of modern data. At the heart of our conversation is the story of the ElectionGraph Project, where Syracuse University used Neo4j's graph technology to investigate political ad spend on Meta platforms. What they discovered was not just political messaging, but sophisticated scams disguised as legitimate campaigns. These efforts, targeting civically engaged users, used merchandise giveaways as a front to harvest credit card details and enroll victims in recurring billing traps. Traditional analytics would have struggled to trace these relationships, but graph databases allowed researchers to map and understand the deeper connections between thousands of entities. We also unpack how graph technology goes far beyond fraud detection. Jim explains why graph databases are now foundational for businesses building AI systems, particularly those using Retrieval-Augmented Generation (RAG) to reduce hallucinations and improve decision making. Whether it's helping enterprises respond to customer needs or enabling AI agents to take action in real time, graphs provide the structure and context needed for reliable outcomes. Jim also shares the backstory behind Klarna's data transformation, where the company embraced knowledge graphs at the core of its operations and replaced major systems, including parts of Salesforce. It's a striking example of what becomes possible when a business commits to connected data as a strategic asset. From misinformation to intelligent automation, this episode dives into the real-world value of graph technology in 2025. Are you thinking critically about how your data infrastructure supports your AI ambitions?

What does digital sovereignty mean in the age of cloud computing, and is Europe finally prepared to rethink its reliance on foreign infrastructure?  In this episode, I speak with David Michels from Queen Mary University of London about his latest research, which examines the growing demand for sovereign cloud services across Europe. Commissioned by Broadcom but developed independently, the report surfaces at a time when regulators, enterprises, and policymakers are all asking tougher questions about who controls data and how. David explains why the concept of a sovereign cloud is still poorly defined. Depending on who you ask, it might mean autonomy over data, protection from foreign surveillance, or strategic independence from global superpowers. That ambiguity creates confusion for customers and raises compliance risks in regulated industries. My guest also addresses one of the most persistent misconceptions in the market: the difference between data residency and data sovereignty. Just because data is stored in Europe does not mean it is immune from foreign access if the provider falls under another country's jurisdiction. We dig into the practical implications of these issues, including why many organizations are reassessing their risk exposure, particularly in light of extraterritorial legal frameworks like the US CLOUD Act. David outlines a pragmatic approach to improve clarity without waiting for new legislation. His proposed GDPR-aligned code of conduct would allow cloud providers to transparently demonstrate compliance with European data protection expectations, giving customers a stronger basis for trust and accountability. This conversation is not about cloud theory. It is about legal risk, operational impact, and policy direction. Whether you're a CIO navigating compliance, a regulator shaping guidance, or a provider building cross-border services, this episode offers a clear-eyed look at the shifting demands of digital sovereignty. Are European organizations finally ready to take a different path in the cloud?

In today’s episode of Tech Talks Daily, I sit down with Jeff Butler, General Manager of Cask Canada, who shares the story of how he led a tech startup to a standout position in the competitive ServiceNow ecosystem in less than a year. Listen in to learn how Cask Canada grew from startup to standout in the ServiceNow ecosystem by focusing on people, trust, and AI-driven transformation. As we explore Jeff’s unique journey from his early days witnessing the birth of Silicon Valley innovation in San Francisco to building a thriving ServiceNow consulting business in Canada, there are lessons here for anyone navigating today’s fast-moving tech landscape. Jeff offers a first-hand look at the unexpected realities of launching a consultancy in Canada's evolving digital market. Rather than focusing solely on technology, he highlights the power of building genuine, long-term relationships with clients and team members. Throughout our conversation, it becomes clear that success in tech services today is shaped as much by trust, patience, and authenticity as it is by technical excellence. We also discuss how AI and automation are reshaping ServiceNow-driven digital transformations. Jeff provides valuable insight into how AI is not just enhancing customer service experiences but also beginning to change the way consulting services are delivered. Yet he makes an important point: human oversight remains vital, especially when high-stakes business decisions are involved. Looking ahead, Jeff reflects on the challenges and opportunities that ServiceNow partners face as AI capabilities mature, integration demands grow, and the implementation partner landscape changes. He also shares how building an elite consulting team required a deliberate focus on culture, communication, and finding people who want to build something bigger than themselves.  

What if contracts could do more than sit in a drawer gathering dust? In today's episode, I sit down with Monish Darda, CTO and Co-founder of Icertis, to explore how AI is transforming contracts into powerful, active business assets. Monish shares how Icertis has evolved from early machine learning models to leveraging large language models like GPT to extract information and true intent from contracts. This breakthrough allows organizations to optimize business relationships, enforce commitments such as sustainability goals, and significantly reduce revenue leakage, often reclaiming up to 9% of contract value. During our conversation, Monish explains how contracts become first-class enterprise objects actively participating in workflows, shaping how commerce operates at scale. We dive into real-world examples, including how a global pharmaceutical company saves over $70 million annually by optimizing supplier pricing across multiple countries and languages. Monish also highlights Humana's success in cutting operating expenses by over $125 million by embedding contract intelligence into core processes. We also unpack the importance of data quality in building trustworthy AI systems. Monish looks at how Icertis ensures clean, actionable contract data through a standard data model, human-in-the-loop verification, and hundreds of thousands of built-in validation rules. As the world rapidly embraces AI, he shares his vision for a future where AI agents are constrained by the "rules of business" defined within contracts, ensuring responsible and reliable decision-making. Monish rounds off our discussion with an inspiring nod to Isaac Asimov and the power of storytelling in shaping our understanding of technology's future. If you ever thought contracts were just static documents, this conversation will change how you see them and reveal how AI is reshaping the foundations of enterprise operations. How is your organization preparing for a future where contracts guide and drive business outcomes?

In today’s episode of Tech Talks Daily, I sit down with Prashanth Chandrasekar, CEO of Stack Overflow, to explore how the rise of AI is reshaping the future of software development and the evolving role of community-driven platforms. Prashanth offers a grounded view of what is happening behind the headlines as the tech world moves into the third year of widespread AI adoption. We begin by unpacking how AI is already transforming the way developers work, automating routine coding tasks, while still falling short when it comes to complexity and trustworthiness. Prashanth explains why Stack Overflow is positioning itself as a community and a vital "Knowledge as a Service" platform, integrating with AI tools to maintain trusted knowledge in an age where data quality and source attribution have never been more important. Our conversation also delves into the growing concern of "LLM brain drain" and the broader data crisis facing AI innovation. Prashanth highlights the importance of human-generated content, even as synthetic data technologies advance. He shares why Stack Overflow's continued investment in community-driven knowledge, responsible AI use, and strategic partnerships with major AI players is critical to maintaining a healthy ecosystem for developers and enterprises. We also look ahead to Stack Overflow's strategic priorities, including expanding content types, integrating AI into both the public platform and Stack Overflow for Teams, and moving toward a seamless user experience across the tools developers already use every day. How can businesses balance automation with human insight in their AI strategies? Why is data scarcity a looming issue for AI development? And how is Stack Overflow preparing to lead community and enterprise solutions into the next era of innovation? Let's find out.

How do businesses untangle years of legacy technology without risking everything they have built? Today on Tech Talks Daily, I sat down with Jacek Migdał, founder and CEO of Quesma, to explore this question and discover how his company offers a fresh and pragmatic approach to database migration and optimization. Jacek shared the story behind Quesma's creation, shaped by his early exposure to databases through his father's work and his own experiences in Silicon Valley. Through extensive research, he identified a widespread frustration among businesses trying to modernize their legacy systems, often facing high costs, licensing nightmares, and failed migrations. Rather than tearing everything down and starting from scratch, Quesma offers a database gateway that acts as a middle layer, allowing gradual migrations with far less risk. I learn more about how this technology enables companies to test new systems alongside their old ones, helping to avoid the costly mistakes that have historically derailed so many modernization projects. We  discussed how Quesma is addressing complex challenges across industries like telecom and travel. Their solution is already providing companies with ten times faster performance while significantly lowering operational costs, all without forcing disruptive system changes. Jacek also gave a sneak peek into two exciting new products launching soon. SQL extensions with pipe syntax will enrich data directly inside databases, while a feature called "smart charts" will offer AI-powered visualizations for faster, clearer insights. What makes Quesma truly stand out is its unapologetically pragmatic approach. Rather than assuming a clean, cloud-native environment, Quesma embraces most businesses' messy realities. Their clever use of AI enhances migration processes without relying solely on black box systems, striking a unique balance between speed, reliability, and cost efficiency. As we look toward the future, Jacek shared how Quesma is pushing forward with open-source initiatives, observability pipelines, and forming consortiums with major players in the tech industry. With upcoming appearances at major conferences in the United States and Europe, it is clear that Quesma is carving a new path for database modernization. How could a smarter approach to data migrations change how your organization adapts and grows in a data-driven world?

When building a successful startup, the difference between thriving and failing often lies in understanding the journey itself. Today, I had the pleasure of speaking with Gregory Shepard, the entrepreneur behind "The Startup Lifecycle" and the founder of the Startup Science platform. Gregory's research-driven insights offer a clear and practical roadmap that challenges the myths that have surrounded startup culture for decades. In our conversation, Gregory shared how his five-year research project revealed why so many startups fail and what can be done to reverse that trend. With data showing that 47.1 percent of startups fail within the first 18 months, Gregory highlights the critical importance of getting the earliest decisions right.  Overvaluation, misunderstanding capital needs, premature scaling, and neglecting to consider an exit strategy from the start are some common missteps he passionately helps founders avoid. Gregory also discussed the seven stages of the startup lifecycle he created, paying particular attention to the often overlooked stages of standardization and optimization.  Rather than rushing from product development to rapid growth, he emphasizes the need to stabilize and streamline operations first to ensure that scaling brings real profitability, not just top-line growth. This mindset shift alone could dramatically alter the success rate of new businesses. Beyond the book, Gregory has built the Startup Science platform, a comprehensive ecosystem designed to give founders access to mentors, investors, grants, classes, and curated resources all in one place. It is not just about reading a book or attending a workshop. It is about systematically embedding success principles into every aspect of the entrepreneurial journey. We also talked about the current startup climate and why economic downturns often lead to a surge in entrepreneurial activity. Gregory's advice is simple yet powerful: bunker down, stay focused, and view this period as an opportunity rather than a barrier. Investors still back good companies even when the broader environment feels uncertain. Throughout our conversation, Gregory's passion for supporting marginalized entrepreneurs and his commitment to the social and environmental impact of startups shone through. His belief that entrepreneurship is a true driver of global progress resonated deeply with me. Every aspiring founder can learn from their structured approach to resilience and success. For those curious about the real factors behind startup success, I highly recommend checking out "The Startup Lifecycle" and exploring the resources available at GregoryShepard.com and StartupScience.io. If you are serious about your entrepreneurial dreams, this is one conversation you cannot afford to miss.

How can computer vision and AI reshape the future of coaching, player development, and fan engagement in sports? In today's episode of Tech Talks Daily, I sit down with Lauren Pedersen, CEO and co-founder of SportAI, to explore how AI brings advanced sports analysis to athletes and coaches everywhere, not just to elite professionals. Lauren shares the inspiring journey that led her from New Zealand to Norway and from NCAA Division 1 tennis player to tech entrepreneur. SportAI is leading a movement to democratize access to professional-grade coaching tools, offering real-time tactical and technical analysis in racket sports like tennis, paddle, and pickleball.  Using computer vision to track body movement and ball contact points from video alone without the need for wearables, SportAI delivers data-backed insights directly to coaches and players through integrations with camera-enabled courts and coaching platforms. We also dive into how SportAI's technology serves sports organizations, academies, equipment brands, and broadcasters, providing valuable performance data and creating new revenue streams for local clubs. Lauren talks about the balance between AI and human coaching, how AI enhances but never replaces the coach's role, and why social engagement and player empowerment are at the heart of this sports technology evolution. Lauren's vision stretches beyond racket sports, hinting at future expansions into golf, basketball, and baseball, wherever repetitive motion training can benefit from biomechanical analysis. As the sports world embraces AI and camera technology at scale, what does this mean for the future of training, competition, and how athletes of all levels experience the game? Tune in to learn how SportAI makes advanced sports insights accessible to all and what lies ahead for this exciting intersection of sports and technology.

In this episode of Tech Talks Daily, I'm joined by Sunil Singhvi, Head of Arts & Culture at TriliTech, the London-based blockchain hub helping shape the future of digital experiences through the Tezos ecosystem. Sunil brings a rare blend of deep tech, culture, and media expertise, having held senior roles at Twitter, Instagram, and Rarible before joining Trilitech. His mission? To explore how blockchain isn't just about tokens and ledgers but about real human connection, particularly between creators, brands, and their communities. What stood out in our conversation is how Sunil views blockchain as a vehicle for restoring creative autonomy and rebuilding trust in the creator-fan relationship. Through compelling examples like Manchester United's Fantasy United game and McLaren's collectible-driven fandom, we explore how Tezos enables ownership, co-creation, and authentic engagement that outpaces traditional social platforms and algorithms. We unpack the evolution of NFTs, moving beyond the speculative bubble of the past into more grounded use cases that offer tangible benefits. From supporting emerging artists through royalty-respecting marketplaces like objkt.com to enabling fans to co-create digital artwork through platforms such as editart.xyz, the conversation highlights a meaningful shift in how digital creativity is produced and experienced. Sunil paints a future where fans become collaborators and artists regain long-lost visibility into who their supporters truly are. We also reflect on the power of community, where smaller and more engaged groups increasingly matter more than vast but disengaged audiences. And perhaps most importantly, we explore what happens when creative expression is no longer dictated by opaque systems but driven by transparent, decentralized tools. Could blockchain finally deliver on the promise of a fairer and more inclusive creative economy? And if so, how can artists, brands, and everyday users participate in this movement without repeating the missteps of earlier digital revolutions? Let us know your thoughts. Could Web3 be the reset button creative industries have been waiting for?