Tech Talks Daily

What happens when early-stage founders realise their go-to-market strategy just isn’t working? Do they double down on outdated advice or take a fresh look at how modern buyers actually engage? In this episode of Tech Talks Daily, I sit down with Richard Lowry, founder of Springboard IQ, to unpack how he’s helping startups rebuild broken GTM strategies in just seven days through a crowdsourced, operator-led model that challenges everything we think we know about growth. Richard explains how Springboard IQ brings together six active operators to co-create a go-to-market blueprint that’s fast, focused, and grounded in the realities of today’s market. This approach delivers practical strategy and design rather than execution, giving founders clarity on where to focus their time and energy. As Richard puts it, founders should save their passion for the demo because that’s where it really matters. The conversation explores why technical founders often mis-hire sales talent, why relying on outdated accelerator advice can derail growth, and why many teams hit a “GTM wall” long before real scale begins. We also discuss why the future of GTM might look very different from the digital-first strategies of the past. As inboxes flood with automated outreach and AI-generated content, Richard believes human-led activation through curated events, community experiences, and even spontaneous moments of connection will define the next era of startup growth. It’s a conversation that blends practical lessons, honest stories (including one involving a soup kitchen in Lisbon), and a call to bring the human element back to how we sell, connect, and grow. So, could a crowdsourcing strategy from active operators be the smarter way for startups to go to market? And in an era of AI-saturated noise, will the next big differentiator simply be showing up in person? I’d love to hear your thoughts after you listen.

What happens when a world-class badminton player trades the court for the courtroom and then the boardroom? In this episode of Tech Talks Daily, I sit down with Tom Dunlop, CEO and co-founder of Summize, to explore how a former Great Britain athlete became one of the most forward-thinking leaders in legal technology. Tom shares how his journey from sport to law to entrepreneurship shaped his leadership philosophy and his belief in “high agency,” the mindset of taking ownership, driving action, and leading from the front. We talk about how that outlook helped him transform the traditional image of legal work into something faster, smarter, and more collaborative through Summize’s AI-powered Contract Lifecycle Management platform. Rather than forcing users to adopt new software, Summize integrates directly into tools people already use like Teams, Slack, Outlook, and Word, embedding contract management seamlessly into everyday workflows. We also explore Tom’s reflections on brand building in a historically conservative industry, the mental shift from risk-averse lawyer to decisive founder, and why he believes legal leaders should embrace innovation as a way to strengthen their role at the boardroom table. His story is as much about personal reinvention as it is about technological disruption, revealing how determination, discipline, and curiosity can reshape even the most traditional professions. So, how do you balance precision with risk when you move from legal advisor to entrepreneur? And what lessons from sport, law, and leadership can help us all perform better in the fast-changing world of work? I’d love to hear your thoughts after listening.

What if the key to creating cleaner, faster, and more efficient cities isn’t building new infrastructure, but rethinking how we move what we already have? In this episode of Tech Talks Daily, I’m joined by Richard Savoie, co-founder of Adiona, whose AI-powered logistics platform is transforming how goods travel through urban environments. Richard’s background as a patent-holding engineer and mentor in the medical device field gives him a unique perspective on precision, quality, and human-centered design. At Adiona, he applies that same discipline to logistics, helping delivery networks run smarter, leaner, and more sustainably. His FlexOps platform uses AI to optimise routes, model EV fleet conversions, and create digital twins of operations so companies can reduce emissions and increase efficiency—without replacing the people who make it all work. In our conversation, Richard shares why he believes in a humanistic approach to AI that empowers drivers, dispatchers, and warehouse workers instead of automating them out of existence. We also explore how Adiona’s scenario modelling helps global brands like Coca-Cola and Australia Post cut costs while meeting 2030 sustainability goals, and what the future might hold as AI and robotics begin to converge for last-meter delivery. So, could the next big sustainability breakthrough come from reimagining the routes that already exist? And how might AI reshape the logistics networks that keep our world moving? I’d love to hear your thoughts after listening.

What if the key to unlocking real AI transformation isn’t a new enterprise platform or an executive directive, but something much simpler: listening to the innovators already inside your company? That’s the idea behind AppDirect CTO Andy Sen’s philosophy on bottom-up AI adoption. In this episode, we talk about why the most effective AI strategies often begin at the grassroots level, led by curious employees who experiment first and ask for permission later. Andy explains how AppDirect built a culture of AI experimentation by giving employees a secure “digital playground” to test ideas, measure results, and scale what works. From developers using AI to write half of the company’s new code to non-technical staff building internal tools, AppDirect’s approach has driven measurable productivity gains while cutting costs and improving efficiency. Rather than dictating from the top, leaders are encouraged to ask questions, support innovation, and apply a “yes, but” mindset that modifies solutions for governance and compliance instead of shutting them down. As organizations everywhere wrestle with how to scale AI responsibly, Andy offers a fresh take on balance by empowering employees to build while ensuring security and oversight. We also explore the rise of developer-focused platforms like devs.ai, which allow teams to safely create agentic solutions across different large language models. So, are your employees already innovating with AI while leadership lags behind? And what might your business discover if you stopped trying to control AI adoption and started observing where it’s already thriving? Let me know your thoughts after listening.

What if artificial intelligence could help you find, value, and buy an online business in minutes instead of months? That’s the idea behind Lauren AI, Flippa’s new proprietary deal origination tool designed to make mergers and acquisitions accessible for everyone, not just the elite few. In this conversation, Blake Hutchison, CEO of Flippa, returns to share how the company is using AI to democratize business ownership for what he calls “the 99%.” Blake explains how Lauren AI indexes over five million digital businesses weekly, analyzing everything from revenue models and tech stacks to traffic and growth potential. Using natural language prompts, it builds a hyper-specific buyer mandate and surfaces opportunities tailored to each individual’s skills, goals, and budget. What used to cost thousands of dollars in retainer fees for M&A analysts can now be achieved with a few clicks and a $1.99 outreach. For Blake, it’s about eliminating friction in the acquisition process while giving everyday entrepreneurs access to real, data-driven deal flow. The conversation also explores Flippa’s new partnership with SeedLegals and the launch of “Flip and Raise.” This initiative helps UK founders perform a Delaware Flip, reincorporating their business in the US so they can raise capital directly from Flippa’s network of 75,000 accredited investors. The result is a more connected global marketplace, where cross border deals are not just possible but encouraged. Across the episode, Blake reflects on his mission to lower the barriers to entrepreneurship, his belief in AI as an enabler of ownership, and the early examples of global deals made possible by the platform. He also shares a personal moment of gratitude for his wife, whose leap of faith from San Francisco to Melbourne mirrors the kind of courage he sees in founders every day. This episode captures the spirit of modern entrepreneurship, tech enabled, global, and deeply human. It’s a story of how AI is quietly reshaping one of the most traditional areas of business, turning mergers and acquisitions into something anyone, anywhere, can take part in.

What happens when the ancient magic of theatre meets the disruptive energy of artificial intelligence? In this episode of The Tech Talks Daily Podcast, I sit down with Emmy-nominated producer and 440 Media founder Jeffery Keilholtz to unpack how AI is reshaping entertainment, licensing, and the very soul of live performance. From his time leading Broadway Licensing Global, home to thousands of acclaimed titles including Harry Potter and the Cursed Child, Jeffery brings a rare blend of creative and commercial insight to one of the most transformative moments in entertainment history. Our conversation explores how live entertainment faces twin challenges of visibility and scarcity in a digital age. As Jeffery explains, the rise of ChatGPT has changed how people search, discover, and decide what to see, forcing a shift from SEO to AEO, or Answer Engine Optimization. Yet even as AI floods the world with abundance, theatre’s scarcity, that irreplaceable “live, local, urgent” energy, is becoming more precious than ever. Together we examine how AI can simultaneously empower and endanger creative industries, from copyright battles worth billions to the promise of smarter audience engagement and new paths to discover hidden works. Jeffery also shares his framework for balancing technology and artistry, urging creators to stay nimble like a blade of grass. He argues that surviving this era of AI-driven disruption requires humility, flexibility, and a renewed belief in human connection. It’s a powerful reminder that the heartbeat of theatre, and perhaps of creativity itself, still belongs to people gathered together in the same room, sharing something that can never be replicated by a machine. How do you see AI reshaping the arts and entertainment world? Is it an existential threat to creativity or the tool that will help artists reach new heights? I’d love to hear your thoughts.

What happens when classrooms become laboratories for artificial intelligence? As AI tools find their way into schools, from lesson planning to student assessments, educators and parents are wrestling with how to balance innovation and security. In this conversation, I sit down with Jurgita Lapienytė, Chief Editor at Cybernews, to unpack how AI adoption in education is reshaping learning, privacy, and the safety of our youngest digital citizens. Jurgita brings a rare dual perspective as both a technology journalist and a mother. We explore how AI’s growing influence could improve access to knowledge while eroding fundamental cognitive skills if introduced too early or without balance. She compares today’s reliance on AI to the way GPS changed navigation, convenient but potentially disorienting when overused. Together, we look at how schools can encourage analog learning before turning to technological shortcuts and why teacher training is crucial for building true tech readiness. But beneath the excitement lies a darker reality. With 82 percent of K-12 schools hit by cyber incidents in the last 18 months, education is fast becoming one of the most targeted sectors. Jurgita explains how AI is supercharging attacks from phishing to deepfakes and why schools must view data protection as an essential part of innovation rather than an afterthought. We discuss the growing risks around student data, the ease with which even innocent photos can be exploited, and why privacy policies need a complete rethink before more AI tools enter the classroom. This episode isn’t about rejecting technology, it’s about using it responsibly. Jurgita’s insights remind us that AI’s value in education depends on how thoughtfully it’s implemented and how prepared we are to protect the people it’s meant to serve. So what does a secure classroom really look like in the age of AI, and how can schools, policymakers, and parents work together to create one? I’d love to hear your thoughts, how should we balance innovation with safety in our children’s digital future?

What happens when simplicity meets AI on the world’s biggest tech stage? In this episode, recorded live at GITEX Global in Dubai, I sit down with Sohaib Zaheer, Senior Vice President and General Manager at DigitalOcean, to talk about how the company is staying true to its founding vision of accessibility and simplicity while entering the age of AI. For years, DigitalOcean has been known as the cloud that “speaks the language of builders,” empowering developers and startups to innovate without unnecessary complexity. Now, with the launch of its Gradient AI platform and Cloudways Copilot, the company is bringing that same philosophy to AI development, helping teams go from idea to production-ready agents without huge DevOps teams or fragmented toolchains. Sohaib explains how DigitalOcean’s unified stack is making AI agent development faster, easier, and more transparent. We discuss the startling statistic that 95% of AI projects never make it past the prototype stage, and explore how Gradient AI aims to change that through agent templates, debugging tools, and built-in guardrails. We also look under the hood at AI inferencing, GPU optimization, and why performance and cost efficiency still matter as much as cutting-edge innovation. If you have ever wondered how AI can become truly accessible, or how simplicity might just be the next big breakthrough, this conversation offers a grounded, real-world perspective from one of the most down-to-earth leaders in cloud technology. Recorded live on the show floor at GITEX Global, this episode is a reminder that great tech is not about hype, it is about helping people build, test, and create with confidence.

I’m taking you behind the scenes of GITEX Global with someone who lives and breathes the energy that makes this event what it is. Daniela Muente, Global Marketing Director at GNX, joins me to share how the world’s largest technology showcase comes together, what drives its incredible growth, and why Dubai has become such a powerful crossroads for innovation. GITEX Global isn’t just another tech conference. It’s where conversations about AI, sustainability, smart cities, cybersecurity, and digital transformation collide with real-world solutions and human stories. With more than 6,800 companies and over 200,000 attendees from across the globe, Daniela explains how her team brings this massive ecosystem to life every year—curating an experience that connects startups, enterprises, governments, and everyday innovators under one roof. In this episode, Daniela reflects on how storytelling, community, and purpose shape the identity of GNX. We discuss how the event celebrates diversity in technology, why the Middle East is fast becoming a global tech hub, and what it takes to orchestrate an event that captures the imagination of the world.

Deepfakes used to be a niche curiosity. Today they have become a sophisticated tool for manipulation, persuasion, and exploitation. In this episode of Tech Talks Daily, I sit down with Aleksander Gorkowienko, Head of Penetration Testing at Risk Crew, to examine how artificial intelligence has transformed deepfakes from playful face swaps into full-scale multimedia attacks designed to deceive even the most vigilant among us. Aleksander explains how we have entered the age of Deepfakes 2.0, where fake video, audio, images, and text merge to create hyper realistic digital experiences. These aren’t the crude social media edits of a few years ago. They are now weaponized as tools for emotional manipulation, exploiting fear, urgency, and trust to trick victims into transferring money, sharing data, or compromising systems. Aleksander walks through real world examples of how criminals build these illusions, using stolen digital footprints to impersonate executives, family members, and trusted colleagues in live video calls. We discuss how AI’s accessibility has accelerated this problem. With free tools and moderate computing power, almost anyone can now create a convincing fake offline. Aleksander shares how this ease of creation erodes trust online, making it harder to distinguish truth from fabrication. He also reveals how attackers rely less on technology itself and more on psychology, engineering scenarios that push people into acting before thinking. From a defense standpoint, Aleksander offers clear, actionable insights. He talks about the importance of multi factor verification, context based awareness, and fostering what he calls “streetwise vigilance” in the digital world. He compares it to walking through a city at night; you wouldn’t flaunt your valuables, so why overshare online? We explore how organizations can conduct training and simulations to teach employees to pause, question, and verify before reacting. This episode is a timely warning for every business and individual operating in a world where reality can be faked in seconds. Aleksander’s rule of thumb is simple but powerful: never trust a single source of information. Cross check, slow down, and think before you act. Because in the age of AI deception, trust must be earned every time. Listen now to hear Aleksander’s firsthand perspective on how deepfakes are changing cybersecurity and what we can all do to stay one step ahead.

What if artificial intelligence could help end world hunger? In this special episode recorded live from GITEX Global in Dubai, I sit down with Magan Naidoo, Chief Data Officer at the United Nations World Food Programme, to discuss how data and AI are transforming humanitarian work at scale. Magan paints a powerful picture of the global food security crisis, where hundreds of millions of people face hunger across more than 80 countries. He explains how the World Food Programme is using technology to predict food shortages, optimise supply chains, and deliver aid faster and more effectively. Behind every algorithm sits a simple goal: getting food to those who need it, when they need it most. We explore how AI models are helping the organisation make sense of enormous datasets, identifying patterns that humans alone could not process quickly enough. From predicting drought-related crop failures to reducing the cost of food delivery through smarter routing, Magan reveals how data-driven decisions are saving both time and lives. He also shares the organisation’s commitment to ethical AI, strong data governance, and privacy protection in every region they operate. As the only UN agency with a formal AI strategy, the World Food Programme is setting a benchmark for how large-scale institutions can use technology responsibly and effectively. Magan’s story highlights the importance of trust, collaboration, and resilience in a mission where failure is not an option. Could AI truly be the key to solving one of humanity’s oldest challenges? And what lessons can every organisation learn from how the World Food Programme blends compassion with computation? Tune in, then share your thoughts.

This week has reminded me why I love what I do. I have spoken with people from the US, China, Dubai, Bulgaria, and South Africa, and even discovered that one of this show’s regular listeners had made the journey from the Netherlands to be here at GITEX Global. Over five sessions on the AI Stage, I have covered everything from autonomous cars to how AI could help the UN World Food Programme tackle hunger. We have explored how Serbia achieved tenfold growth through AI and how new tools can now verify misinformation simply by checking a video link. But beneath all the tech talk, what has stood out most to me is how technology connects people. In a world that often feels divided, it is refreshing to see how collaboration and shared curiosity can still bridge cultures and spark ideas. It is those moments, when technology brings people together, that remind me why this podcast exists. That spirit of connection is exactly what inspired my quick chat with Iancho Dimitrov from Living Homes, a company based in Dubai but shaped by global perspectives. Originally from Bulgaria, Iancho and his team are building what they call an “AI-native intelligent home,” a home that does not just automate switches but truly understands its inhabitants. From monitoring wellbeing and improving sleep to creating safe, supportive spaces for families across generations, Living Homes is redefining what it means to live smart. So while this conversation might be short, it captures something powerful. It is proof that innovation is not only about hardware or software, it is about empathy, understanding, and the shared drive to build a better way of living. In a week where the world gathered in one city to imagine the future, Iancho’s vision is a reminder that technology works best when it feels human.

What if the next generation of computing was not something you held or wore, but something you looked through? In this special episode recorded live from GITEX Global in Dubai, I speak with Roman Axelrod, founder of EXPANCEO, a deep tech company creating AI-powered smart contact lenses designed to merge augmented reality, biosensing, and what he calls digital superpowers. Roman explains how his company moved from an ambitious idea to becoming the first deep tech unicorn in the Gulf region, now valued at more than 1.3 billion dollars. Over the past five years, his team of physicists and engineers in Dubai has built more than fifteen prototypes and secured a wide range of patents, all aimed at developing what they see as the ultimate interface for AI-driven computing. These lenses can display digital images, measure biological signals such as glucose and intraocular pressure, and may one day eliminate the need for screens altogether. He reflects on the early days of disbelief, when even friends told him to give up, and how perseverance became the deciding factor. For Roman, success meant proving that deep tech innovation is possible outside Silicon Valley. He shares how Dubai’s ecosystem, low taxation, and access to world-class talent helped make that vision real. His story offers practical insight for founders who are told their ideas are impossible until they can show a working prototype. We also explore what this means for the future of human-computer interaction. Roman believes these lenses will help us communicate directly with intelligent systems, turning science fiction into everyday life. His message to entrepreneurs is simple: be stubborn, stay curious, and keep building. Could AI contact lenses redefine computing itself? Listen to the conversation and share your thoughts.

What if the real breakthrough in AI isn’t the model itself, but the data that gives it knowledge? In this episode of Tech Talks Daily, I sit down with Edo Liberty, founder and Chief Scientist of Pinecone, to unpack how vector databases have quietly become the backbone of modern AI infrastructure. We explore why retrieval-augmented generation (RAG) works so effectively out of the box, and why fine-tuning large models often adds complexity without real-world value. Edo shares how Pinecone’s research revealed that different models—from OpenAI to Anthropic—require differently structured context to perform well, a discovery that’s reshaping how enterprises think about AI implementation. As the former Director of Research at Yahoo and AWS, Edo offers a grounded perspective on where the real innovation is happening. He explains how the shift from traditional data structures to vector representations is redefining how machines “know” and retrieve information, creating smarter, context-aware systems. We also touch on his recent transition to Chief Scientist, his excitement for returning to hands-on research, and why he believes the convergence of AI and data represents the defining technological shift of our lifetime. So, what does it mean for developers, business leaders, and anyone building with AI when knowledge becomes an accessible layer of infrastructure? Can we build systems that truly “know” as humans do? Join the conversation, and after listening, I’d love to hear your thoughts—do you think the future of AI lies in the models or in the data that feeds them?

What happens when an AI strategy meets the real-world complexity of healthcare, law, and finance? That’s the challenge at the heart of my conversation with Mark Sherwood, CIO of Wolters Kluwer, a global leader in professional information services. With over three decades in technology leadership across Microsoft, Symantec, and Nuance, Mark brings a rare combination of enterprise depth and hands-on pragmatism to the AI discussion. Mark explains why cloud-native architecture and data governance are the twin foundations of trustworthy AI. He shares how Wolters Kluwer is embedding AI across highly regulated industries—from helping doctors access life-saving insights through natural language queries to giving tax and legal professionals faster, more accurate guidance on complex regulations. Behind the innovation lies a disciplined approach: governing data, managing risk, and building confidence in AI systems that must meet the highest standards of accuracy and compliance. We also explore how to build high-trust, low-friction partnerships between IT and business teams to prevent shadow IT while accelerating digital transformation. Mark offers candid insights into the rise of AI agents, the emerging risks of quantum security, and why he believes that high-quality data is the most valuable currency in digital transformation. His philosophy is simple: speed means nothing without trust, and trust starts with clean, well-governed data. From cloud transformation to the future of AI regulation, this episode offers a grounded look at how global enterprises can scale responsibly in an era where innovation often outruns policy. So as AI becomes inseparable from how professionals think and work, how do we balance speed with stewardship? And are we truly ready for the ethical, technical, and quantum frontiers ahead? Share your thoughts after the episode.

What does it take to build AI that enterprises can actually trust? That’s the question I explored with Nirankush “Kush” Panchbhai, Senior Vice President of Platform Fundamentals at ServiceNow, in a conversation about AI governance, human-centered design, and how the company’s AI Control Tower is reshaping enterprise adoption. Kush describes the AI Control Tower as an “air traffic controller” for AI agents, a central command center that provides visibility, accountability, and governance across every part of an organization’s AI ecosystem. It embeds compliance, legal, and risk workflows directly into the development process, replacing endless approval cycles with automated guardrails that accelerate innovation rather than slow it down. The result is a system where humans remain firmly in control, supported by transparent, explainable AI that acts as a teammate rather than a tool. We also discuss how ServiceNow is helping enterprises move beyond the “POC palooza” of pilot projects that never scale. By treating AI agents as members of a digital workforce—with performance tracking, retraining, and measurable ROI—companies can finally connect investment to real outcomes. Governance, in this context, isn’t a constraint; it’s a catalyst for confidence and adoption. At its core, ServiceNow’s philosophy is about taking the work out of work, not the human out of work. From password resets to process automation, AI is freeing employees to focus on creative, high-value problem-solving while building trust through transparency and accountability. As organizations begin managing both human and digital workforces, one question lingers: can AI governance truly become the accelerator that turns trust into enterprise-scale transformation? And what does it take to ensure AI always serves people, not the other way around? Share your thoughts after the episode.

What if the biggest sustainability challenge in tech isn’t hardware or cloud emissions, but the invisible mountain of unused data sitting in storage? That’s the question driving my conversation with Piero Gallucci, Vice President and General Manager for NetApp UK and Ireland, as we discuss how single-use data is quietly shaping the environmental and financial footprint of enterprise IT. Piero explains that 38 percent of stored data is never used again, yet it continues to consume energy and resources indefinitely. He describes how this digital hoarding—often driven by regulatory caution and the overvaluation of data—has become one of the most overlooked contributors to emissions in modern infrastructure. With the rise of AI accelerating data growth by an estimated 50 percent, the challenge is no longer simply about capacity but responsibility. Through examples such as Aston Martin Formula One and the NFL, Piero outlines how NetApp is helping organizations identify unused data, automate lifecycle policies, and design intelligent, energy-efficient infrastructure that supports both innovation and sustainability. We also explore the tension between AI adoption and environmental impact. As enterprises rush to train new models, Piero argues that smarter data governance, not bigger datasets, is the key to sustainable AI. He highlights the importance of educating teams on the true cost of data—both financial and environmental—and why leaders must build intentional strategies that align performance with purpose. NetApp’s vision is clear: make data management as sustainable as it is powerful. But as AI reshapes how we store and use information, can the tech industry finally balance digital growth with environmental stewardship? And what would your company look like if every byte of data had to justify its existence? Share your thoughts after the episode.

What if the next big leap in business AI isn’t generative at all, but predictive? That’s the question at the heart of my conversation with Zohar Bronfman, CEO and co-founder of Pecan AI, a company helping business teams forecast outcomes with precision and turn historical data into future insights. Zohar explains why he believes predictive AI will deliver far greater enterprise value than the generative models dominating headlines. He points to research showing that most generative AI projects fail to produce ROI, while predictive systems built on a company’s own data can directly improve revenue, reduce churn, and guide smarter decisions. With Pecan’s no-code platform, marketing and operations teams can now create predictive models without needing data scientists—bridging the gap between technical expertise and business execution. Through stories like Little Spoon’s, a direct-to-consumer baby food brand that used Pecan AI to identify and retain at-risk customers, Zohar illustrates how predictive analytics turns data into real business impact. He also shares common mistakes companies make when implementing AI—starting with unclear objectives and misaligned resources—and why success depends on defining the problem before choosing the tool. Looking ahead, Zohar envisions predictive AI as the backbone of every organization, shifting business intelligence from reactive analysis to proactive action. As companies move beyond dashboards and toward dynamic decision-making, predictive insights may soon become as fundamental as spreadsheets. So, if your company could anticipate every challenge before it happened, how different would your strategy look? And are business leaders finally ready to treat predictive AI as core infrastructure rather than a passing trend? Share your thoughts after the episode.

What happens when artificial intelligence meets the everyday heroes of local government? That’s the question driving my conversation with Justin Dennis, co-founder and COO of Urban SDK, a geospatial AI company helping more than 250 North American cities make faster, safer, and smarter decisions. Justin shares how a Smart Cities Challenge from the U.S. Department of Transportation inspired him to co-found Urban SDK in 2018, and why he believes the future of public safety depends on replacing manual data collection with real-time intelligence. From traffic fatalities to hurricane recovery, he explains how the company’s HALO platform gives local leaders and emergency responders the insights they need to act before crises escalate. In a single platform, they can identify dangerous road zones, predict high-risk intersections, coordinate clean-up operations, and rebuild infrastructure based on data rather than guesswork. We also explore how AI is quietly reshaping government operations, from disaster management to traffic enforcement. Justin discusses the challenges of introducing cutting-edge technology into systems that still rely on spreadsheets and siloed workflows. Yet his optimism is clear. He believes governments are beginning to embrace AI not as a buzzword but as a practical tool to save time, resources, and lives. As one Florida community recently reported a 40 percent drop in traffic fatalities, the impact is already measurable. Urban SDK’s story is about technology meeting public service with purpose. So as we enter another year of rapid AI progress, how can data-driven insights continue to empower local leaders to protect citizens and improve quality of life? And what could your city achieve if every decision were powered by real-time intelligence? Share your thoughts after the episode.

Two years after our last conversation, Raj Koneru, CEO and Founder of Kore.ai, returns to discuss how the world of AI has changed and how much of it still needs to. When we first spoke, conversational AI was promising. Now it is powering over a billion interactions every day for companies like LG, Coca-Cola, and Blue Cross Blue Shield. Yet Raj argues that the next real breakthrough will not come from novelty, but from accessibility. In this episode, Raj explains why the future of AI depends on open collaboration rather than vendor lock-in. Kore.ai’s partnerships with Microsoft, AWS, and G42’s Inception in the UAE reflect a commitment to interoperability and shared innovation. He offers a rare look into what happens “above the line,” where enterprises actually design and deploy AI agents, compared to the massive “below the line” investments driving the hardware, cloud, and model layers of AI. For Raj, platforms like Kore.ai act as the bridge, translating technical potential into business outcomes. We also explore what true democratization of AI looks like in practice. Raj believes no-code platforms are key to giving both large and small businesses the power to build their own agents without deep technical skills. He discusses the challenges of scaling responsibly, managing latency, ensuring governance, and keeping AI secure and transparent. From the shift toward on-device AI in smartphones to the lessons learned from running one of the world’s largest enterprise AI platforms, his perspective blends realism with optimism. This conversation is a reminder that progress in AI will not be defined by who owns the biggest model but by who makes the technology usable, ethical, and open to everyone. Raj’s message is simple but powerful: read widely, question everything, and collaborate boldly.