Tech Talks Daily

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.

Sunil Singhvi, Head of Arts & Culture at TriliTech, merges tech with culture, drawing from his extensive background at Twitter, Instagram, and the BBC. In this conversation, he highlights how blockchain fosters deeper artist-fan connections and shifts the NFT landscape into more practical realms. Sunil shares compelling examples like Manchester United's Fantasy United and McLaren's innovations, showcasing how digital ownership empowers creators. He envisions a future of collaboration where fans not only support but co-create, reigniting trust and visibility in the arts.

In today's episode, I sat down with Mary Hamilton, Global Lead for Accenture's Connected Innovation Centers, to explore how the landscape of artificial intelligence is shifting. As we mark the 25th anniversary of Accenture's Technology Vision report, this year's insights reveal a profound transition into an era of AI-powered autonomy—reshaping how enterprises operate and how people and technology work together. Mary took us inside the key findings from the Tech Vision 2025 report, which is centered on the growing role of AI as a true partner rather than just a tool. From acting as a co-developer to becoming a brand ambassador and even powering robotics in the physical world, AI is on a fast trajectory toward becoming a foundational layer across every business function. However, Mary made it clear that technology alone isn't enough. Without trust in the systems being built, none of this innovation will land as intended. As she shared, building confidence in AI must be both cognitive and emotional—leaders must ensure that AI systems behave in expected, transparent ways and that people feel confident in their interactions with them. We also discussed how enterprises can harness what Accenture calls "cognitive digital brains" through multi-agent systems that enable intent-driven rather than instruction-led technology. Mary unpacked how these architectures, combined with AI platforms like GenWizard and SynOps are already transforming how companies create, operate, and innovate. We explored how brands can differentiate themselves in an AI-first world, where intelligent systems increasingly mediate customer interactions. She explained that one of the most significant risks is that ever sounds sound the same unless companies inject their values and personality into their AI experiences. We also touched on the rise of general-purpose robots, which have gained specialist capabilities and brought flexibility to logistics and manufacturing. Through examples with companies like KION and Schaeffler, Mary described a future where AI-enhanced robots work alongside humans in more agile, adaptive ways Finally, we tackled the human side of adoption. Mary shared why upskilling employees, giving them time to experiment, and aligning culture with AI goals are vital for lasting impact. Measuring success in this space requires more than cost savings or productivity gains. Ethical compliance, trust-building, and workforce empowerment are also essential signals that businesses are moving in the right direction. So, what does it take to turn AI from a buzzword into a practical driver of reinvention? How can leaders build a digital foundation ready for a future defined by autonomy and intelligence? Tune in to hear how Accenture is answering those questions—and helping the enterprise world do the same.

Kim Storin, the new CMO at Zoom, dives into the future of work, bringing years of branding expertise to the table. She discusses how Zoom is evolving from a video conferencing tool to a full-fledged collaboration platform. Storin emphasizes the shift in customer engagement, noting that today's consumers often complete their research before speaking with sales. She also sheds light on the importance of balancing automation with human connection, and how generative AI is reshaping marketing strategies and brand storytelling.

What does it really take to modernize an enterprise in a world of constant disruption, increasing AI capabilities, and evolving customer expectations? In this episode of Tech Talks Daily, I sit down with Rajsekhar Datta Roy, Chief Technology Officer at Sonata Software, to explore how modernization engineering and responsible AI adoption are reshaping business transformation strategies. Raj brings decades of experience to the conversation, guiding organizations through the complexities of aligning technology with business value. We begin by unpacking what modernization truly means in today’s environment. Rather than a single event, Raj explains how modernization is a continuous process that blends operational efficiency with agile frameworks and a readiness to adapt to future technologies like AI.  My guest shares Sonata Software’s structured approach to modernization, designed to generate efficiency from existing systems and redirect those savings into smarter, faster innovation cycles. We also explore the growing role of generative AI in digital transformation. Raj outlines the importance of moving beyond surface-level applications, advocating for a deeper integration of AI into reimagined business processes. He discusses Sonata’s responsible-first approach to AI, including its governance framework and platform-level deployment strategy that ensures secure and ethical implementation.  The result is not only a future-ready enterprise, but one that can deliver measurable value through better customer experiences, faster decision-making, and scalable AI adoption. As we zoom out, Raj highlights key ecosystem shifts, such as the growing importance of cross-industry collaboration and transforming customer expectations in the age of intelligent agents. He also offers advice on how to modernize without disrupting core systems, emphasizing the value of continuous learning, hands-on experimentation, and practical frameworks that reduce time to impact. If your organization is navigating digital transformation or exploring responsible AI deployment, this conversation offers both a strategic lens and real-world examples to help you move forward with clarity. How are you preparing your technology stack and business processes for what comes next? Let’s continue the conversation.

With over 100 million packages recycled since its launch in 2019, Bower has proven that incentivizing people with real-world rewards can significantly increase recycling rates without building new infrastructure. From barcode scanning to AI-powered image recognition, the Bower app empowers users to recycle all types of packaging and earn rewards simply by dropping items into ordinary recycling bins. It’s simple, scalable, and working across more than 170 countries. Berfin Mert, co-founder and COO of Bower, explains how their latest innovations now detect items without barcodes, such as coffee cups, cigarette butts, and batteries. She shares how AI-driven guidance has led to a 32% improvement in sorting rates, and why location-based data is key to building smarter, more responsive recycling systems.  We also discuss the realities of building a circular economy, the growing role of brands like Nestlé and Varta, and why a purely sustainable pitch isn’t always enough to bring companies on board. Berfin’s perspective on bridging environmental goals with business realities makes this conversation stand out. She talks openly about expanding their value proposition to include marketing insights and loyalty tools, making the platform attractive to both eco-conscious users and revenue-driven brands. Toward the end of our chat, Berfin opens up about her own journey, crediting her brother and co-founder as the person who inspired her to take the leap into entrepreneurship. It’s a grounded, honest look at innovation, impact, and the people who help bring both to life. This episode offers a fresh, practical perspective if you’ve ever wondered how small tech-driven actions can influence global sustainability. Could your packaging be worth something more? Let’s find out together.

Here’s the thing: we all heard Sundar Pichai say that the easy wins in AI have faded and that we may see fewer headline‑grabbing releases from the big players over the next year. That comment feels like a red flag for momentum, but I see it as a green light for action.  In this episode, I chatted with Rahul Pradhan, VP of Product and Strategy at Couchbase, about how teams can take advantage of this pause to move projects from simple experiments into solid, production‑ready services. I ask why many organizations hesitate to send their data to public AI endpoints. Rahul explains that when you’ve invested years building data platforms, handing over your proprietary information—even in encrypted form—can feel like handing over the keys to your kingdom. He walks us through how running models inside your security perimeter keeps private data safe and brings up model accuracy since you can tailor inputs and scrub out noise before it ever reaches the inference engine. Next, we tackle the question of stability. Companies often assume that the path to a live service is straightforward once a pilot works. Rahul warns that managing GPUs, orchestrating models, and serving them at low latency all require skill sets that live at the crossroads of ML engineering and traditional software development. We round out our conversation by shifting focus from tools to teams. Technology alone cannot carry an AI initiative. We need leaders who set a clear vision, data stewards who govern every data flow, and developers who feel as comfortable writing database queries as they define training pipelines. Rahul offers thoughtful advice on building that culture and shares examples of industries—healthcare, financial services, and retail—where the most far‑reaching uses of AI are taking root. If you’re wondering how to push your proof of concept into a robust service that customers depend on, this episode is for you. I promise you’ll come away with ideas you can apply tomorrow and a fresh view of why a little breathing room in AI releases can become the launch pad for your subsequent big success.    

In this episode of Tech Talks Daily, recorded live at Team '25 in Anaheim, I sit down with Jamil Valliani, Head of AI Products at Atlassian, to unpack the momentum behind Rovo, Atlassian’s bold move to reimagine collaboration through generative AI. But this conversation goes far beyond product features. It offers a glimpse into how AI is reshaping teamwork, decision-making, and even company culture. Jamil explains how Rovo brings together enterprise-grade search, secure contextual chat, and a new Agent Studio designed to help anyone, from engineers to HR teams, build their own AI teammates. Perhaps most notably, all of this is being rolled out at no additional cost to Atlassian’s paid users. That shift in accessibility marks a clear intent to drive meaningful adoption, not just feature excitement. We explore why 2025 is being tipped as the year of the AI agent, and how Atlassian is helping businesses move beyond overwhelm and into action. What stands out is how teams are using Rovo not just to save time but to remove the friction that clogs up workdays. Think triaging support tickets, updating status reports, or turning customer insights into ready-to-execute tasks. These are no longer chores left to team members; they are responsibilities shared with intelligent, learning agents that work alongside them. Jamil also shares some revealing stats. Customers are already seeing up to 2x return on investment, saving over 100 minutes a day, and 85 percent say the quality of their work has improved. That time and mental clarity is giving teams space to experiment, adapt, and create. So, where should you begin if you're starting your AI journey? And what does it take to build a culture where AI is embraced not just as a tool, but as a catalyst for better work? Tune in, and let us know what your AI-powered future looks like.