What changes when a retailer can make a separate decision for every customer instead of placing thousands of people into the same campaign segment?

In this episode of Startup Builders & Backers, I speak with Ilyas Kurklu, CEO and co-founder of Replenit, about the company’s attempt to move retail CRM beyond fixed audiences, campaign calendars and generic promotions. Replenit calls its product Maestro, an AI CRM Manager designed to decide what should happen next for each customer and pass that decision to the retailer’s existing channel tools.

The distinction between prediction and decision runs through our conversation. A propensity score can estimate what someone might do, but a retailer still has to decide whether to act, which product to recommend, when to communicate and whether a discount is commercially sensible. Ilyas argues that this reasoning should be readable by a human CRM manager. For every decision, the team should be able to inspect why this customer was selected, why the timing was chosen and why a particular product was recommended.

That raises the question every enterprise AI project eventually faces: how do you prove the system created value rather than claiming credit for a purchase that would have happened anyway? Ilyas recommends measuring incremental margin per customer against a randomized holdout. He is skeptical of attributed revenue, influenced revenue and open rates when they do not reveal whether the business made additional money. We also discuss Replenit’s focus on cost per decision and the processing expense that comes with adding further data to an AI model.

Integration is another part of the story. Retailers may already use a customer data platform, a customer experience platform, analytics products and multiple communication channels. Replacing that stack can bring cost, delay, security reviews and regulatory work. Ilyas explains why Replenit has been designed as a reasoning and orchestration layer that works with the systems a retailer already owns.

The conversation also considers customer interest and commercial pressure. A retailer may have contractual brand rules, margin targets and limits on which products can be recommended together. Maestro records brand, product and customer memory, while the retailer sets the rules that govern its output. The human CRM manager then becomes responsible for reviewing outcomes, setting boundaries and questioning the system’s decisions.

For founders and backers, Ilyas offers a refreshingly practical reminder. Building an AI company still means doing the ordinary work of running a business, proving that the buyer can make or save money, answering why an incumbent cannot easily copy the idea and reducing the risk that stops an enterprise customer from saying yes.

Would you trust an AI CRM manager to make individual customer decisions, and what evidence or controls would you require before giving it that responsibility? Share your thoughts with me at Tech Talks Network.

What can founders learn from a healthcare workflow that large organizations and independent clinics were both struggling to fix?

In this episode of Startup Builders & Backers, I speak with Charlie Jordan, founder and CEO of VITL, about identifying overlooked customer problems, building technology for legacy markets, and making complicated systems feel simple without weakening trust or compliance.

Charlie’s route into healthcare began during the rapid growth of telehealth in 2020. He later saw compounding pharmacies face a sharp rise in demand, driven in part by direct-to-consumer healthcare and GLP-1 treatments. Fulfillment systems that worked at one volume could quickly develop long backlogs. Prescribers were also entering the same information repeatedly, sending prescriptions into workflows with limited visibility, and spending time chasing pharmacies for updates.

The business opportunity became clearer when Charlie moved from large telehealth organizations to independent practices. The smaller clinics were experiencing the same problems but had far fewer resources available to solve them. If organizations with large budgets and practices with small budgets were both stuck, he reasoned that the workflow itself needed a different answer.

VITL connects cash-pay clinics with verified compounding pharmacies and gives practices a single place to prescribe, compare options, and follow fulfillment. Charlie says the platform has reduced the initial prescribing process from roughly four and a half minutes to 30 seconds. He argues that the larger saving comes after the prescription is written, when status checks, problem resolution, shipment updates, and patient communication would otherwise create hours of additional work.

Speed, however, cannot be separated from responsibility. Compounded medications may carry serious consequences, and Charlie believes the market needs clearer ways to describe and verify quality. He explains how VITL reviews pharmacy standards and ingredients before presenting practices with a network they can use. The aim is to make the experience easier while keeping the checks that protect clinics and patients.

We also discuss Charlie’s design philosophy of beautiful simplicity. His teams ask how little information is needed to complete a task and how few steps a workflow can contain. Repeated data entry is a warning sign. Information collected during patient intake should move through the prescribing process rather than being typed again across several screens.

For founders, Charlie’s most direct lesson concerns uncertainty. Failure is part of building, and no founder will know the answer to every question. The skill is choosing a direction quickly, gathering evidence, and changing course when the decision proves wrong. That lesson becomes especially important in regulated markets, where progress must balance speed with responsibility.

The supplied company brief says VITL works with over 700 clinics and announced a $7.5 million Series A led by SignalFire in March 2026. The scale gives Charlie’s discussion a practical context, but the wider idea applies to any founder facing a market weighed down by old systems and manual work.

Where has your industry accepted unnecessary complexity, and what would it take to redesign that experience around the people doing the work? Listen to the conversation and share your thoughts with me.

What happens when founders can build faster than business buyers can adopt?

In this episode of Startup Builders & Backers, I speak with YouMon Tsang, founder and CEO of ChurnZero. YouMon has built four companies and completed three successful exits, giving him a candid perspective on category creation, B2B market timing, AI adoption, and the confidence required to continue when the outcome remains uncertain.

YouMon believes entrepreneurial founders often run ahead of the market. They see the technical opportunity, create a new category, and then discover that business customers need time to understand the problem, assign an internal owner, approve a budget, and decide what evidence they require. He now sees a strong case for arriving second or third, when buyers recognize the category but remain open to a better answer. It is a useful counterpoint to the startup belief that being first automatically produces a lasting advantage.

We also discuss how AI is changing customer success. ChurnZero works with customer teams focused on retention, expansion, and customer experience. Automation has supported go-to-market teams for years, but agents can now handle decisions and tasks that once required manual review. The important question is when software should recommend an action, when it should complete that action, and what information it needs before the result can be trusted.

For YouMon, the answer begins with data. He separates customer data into facts and information. Facts include contract dates, spending, and points of contact. Information includes call transcripts, emails, product documentation, and knowledge about how the customer uses a service. An AI system needs both to produce a useful recommendation. A clean account record cannot compensate for missing conversation history, while a detailed transcript is of limited value if the system has the wrong contract or contact data.

That combination also affects timing and empathy. Customers quickly notice an automated message that arrives at the wrong moment. YouMon argues that poor timing usually exposes missing information or a badly designed workflow. The language of an email can be tailored, but an empathetic message sent at an inappropriate time remains a poor customer experience.

Trust must be earned gradually. YouMon compares today’s AI agents with the earlier adoption of rule-based automation. Teams initially asked a person to approve each message, then removed that checkpoint after the workflow repeatedly behaved as expected. Organizations can take the same approach with agents. Some may permit immediate action, while others will keep a person in the loop until the business has enough evidence to feel comfortable. The right boundary will vary by company, customer, and consequence.

Founders selling AI must also recognize that buyers require different forms of proof. An early adopter may try an interesting technical answer with limited evidence. A fast follower may want a strong demonstration and one or two customer examples. The wider market will expect social proof, controls, and clear evidence of success. A founder therefore needs to understand where the buyer sits before deciding which argument, metric, or reference will earn confidence.

The conversation closes with YouMon’s view of entrepreneurial uncertainty and a personal story from a difficult fundraising period. Before another investor meeting, he looked in the mirror and changed the question from whether someone would invest to which investor would be lucky enough to join the company. The business had to earn support, but his posture changed from asking for permission to presenting an opportunity he believed had genuine value.

Do founders gain the greater advantage by creating a category, or by arriving later with a better answer when customers are ready to buy? Listen to the episode and share your thoughts with me.

Can a startup launched with £180 grow into a global business serving some of the world’s largest companies?

In this episode of Startup Builders & Backers, I speak with Connor McKenna, co-founder and CEO of Go Swag. His story begins in a Glasgow software agency, where he and co-founder Ben wanted to create a memorable first day for a new employee arriving from Italy.

The welcome gift made an immediate impression and was shared across social media. When Connor suggested creating the same experience for every new employee, colleagues explained how difficult the process would be to repeat across the company.

Connor and Ben searched for a corporate gifting provider capable of managing design, sourcing, branding, logistics, and international delivery from beginning to end. When they could not find one, they launched Go Swag with approximately £180.

Their lack of corporate gifting experience became an advantage because they approached the industry from a software background. Previous work involved building digital products for slow-moving sectors such as banking and pharmaceuticals. Go Swag applied the same thinking to an industry where administration traditionally increased alongside revenue.

Connor explains the company’s DRY principle, meaning “don’t repeat yourself.” Administration, quoting, and logistics should be handled by software, allowing employees to concentrate on customer relationships and creative decisions.

This approach helped Go Swag grow without increasing headcount at the same rate as revenue. Neil notes during the interview that the business has achieved five consecutive years of triple-digit growth with a team of approximately 30 people in Glasgow.

We also discuss why the founders decided to build globally from day one. Corporate gifts sent to employees in India or South America should provide the same experience as packages delivered to London or San Francisco. Scotland’s smaller domestic market also encouraged the team to think internationally earlier than many startups.

Operating globally introduced difficult questions involving customs, tariffs, taxation, warehousing, and logistics. Go Swag launched in 2019 and subsequently faced COVID, Brexit, the UK mini-budget, rising energy prices, and changing tariffs. Connor jokes that he began the company with hair, which provides an unofficial measure of the pressure involved.

For founders pursuing enterprise customers, Connor advises against entering meetings apologetically. Large companies care about consistency, ownership, problem resolution, and avoiding surprises. A startup’s smaller size can offer an advantage because its team can move faster and provide forms of support that larger competitors struggle to approve.

Connor also discusses the discipline required to reject revenue. Smaller contracts may feel attractive during the early stages, but they can consume the time needed to pursue enterprise opportunities. He applies the same thinking to warehouses, international offices, and other investments that might impress people without solving a customer problem.

The conversation closes with Go Swag’s use of generative AI. Connor describes the “blank canvas problem” facing buyers presented with thousands of products and finishing options. Go Swag is developing models that begin with the buyer’s intended outcome and recommend an appropriate gift rather than expecting the customer to become an expert in printing techniques.

Could your startup grow faster by automating repeatable work, rejecting distracting revenue, and approaching enterprise customers with greater confidence? Listen to the episode and share your thoughts with me.

Have you ever tried to book a tennis, pickleball, padel, or squash court and wondered why the process still feels stuck in another decade?

In this episode of Startup Builders and Backers, I sit down with Daren Hornig, founder and CEO of CourtsApp, to discuss how he spotted a major gap in one of the world's fastest-growing sports sectors and decided to do something about it. Drawing on decades of experience in real estate development and sports infrastructure, Daren set out to build what he describes as the Expedia of racquet sports, a platform designed to make finding, booking, and enjoying courts as simple as booking a hotel room.

Daren shares the origin story behind CourtsApp, from acquiring and revitalizing the historic Port Washington Tennis Academy to helping expand pickleball facilities across the Northeast. Along the way, he discovered a fragmented industry filled with disconnected systems, unanswered phone calls, and missed opportunities for both players and operators.

We also explore how artificial intelligence is changing the experience for clubs and players alike. Daren explains the role of Courtney, CourtsApp's AI-powered assistant, and how AI can help facilities improve customer service, reduce operational costs, and create more seamless experiences without requiring expensive technology teams or infrastructure investments.

Beyond the technology, this conversation is packed with lessons for founders. Daren talks openly about building globally distributed teams, moving from physical real estate projects into software development, and why speed, adaptability, and a willingness to solve real-world problems continue to create opportunities in unexpected places.

Whether you're a startup founder, sports enthusiast, investor, or simply fascinated by how technology is modernizing traditional industries, this episode offers an insightful look at what happens when entrepreneurship meets a market ready for change.

Could racquet sports become the next industry transformed by digital platforms and AI? I'd love to hear your thoughts.

Have you ever wondered what separates entrepreneurs who survive economic crises from those who thrive because of them?

In this episode of Startup Builders & Backers, I sit down with Russell Attwood, CEO of Route 101, whose entrepreneurial journey spans multiple decades, technology shifts, and economic cycles. From launching a business in a cupboard room to building and selling a multi-million-pound company, Russell's story offers a candid look at resilience, leadership, and the realities of building companies when conditions are far from ideal.

Russell shares how the 2008 financial crisis forced difficult decisions, including restructuring a successful business to ensure its survival, and how those experiences shaped his approach to leadership, cash flow management, and long-term growth. Rather than viewing entrepreneurship through the lens of overnight success, he offers a refreshing perspective on navigating uncertainty, backing yourself when others doubt you, and building teams that can weather challenging times together.

We also explore the story behind Route 101, a company name inspired by a family road trip down America's famous Highway 101, and how Russell spotted the shift from traditional technology projects to recurring cloud-based services long before many competitors. That insight helped shape Route 101 into a fast-growing customer experience and contact center specialist serving organizations across the public and private sectors.

The conversation naturally turns to one of the biggest topics facing businesses today: artificial intelligence. Russell explains why so many organizations are rushing headlong into AI without first putting the right foundations in place. He discusses the importance of customer knowledge, governance, and practical use cases that deliver immediate value, from agent assistance and call summarization to quality assurance and conversational AI.

Throughout our discussion, Russell brings a balanced perspective to customer experience, reminding us that while technology continues to evolve, customers still want the same thing they have always wanted: a simple, frictionless experience that solves their problems quickly and effectively.

Whether you're building your first company, scaling an existing business, or trying to separate genuine innovation from industry hype, this episode offers valuable lessons from someone who has successfully navigated multiple waves of change while keeping customers at the center of every decision.

What can today's founders learn from someone who has already survived the storms, rebuilt stronger, and chosen to start all over again?

What does it take to build, scale, sell a company, step away from business, and then return because you believe an entire industry is about to be reinvented by AI?

In this episode of Startup Builders and Backers, I spoke with David Amsellem, founder of luxury concierge company John Paul and now Chief Distribution Officer at HBX Group, about entrepreneurship, innovation, and why the next generation of founders will win by orchestrating ecosystems rather than simply building standalone products.

David’s story is particularly fascinating because it spans two very different startup eras. He launched his first company at a time when entrepreneurs still had to justify why they weren’t pursuing traditional careers. Today, he sees a completely different environment where speed, agility, AI, and access to capital are changing how startups compete against much larger organizations. But despite all the technology shifts, he believes the entrepreneurial mindset itself remains remarkably unchanged. Founders still need resilience, conviction, adaptability, and the willingness to keep moving when nobody else believes in the vision yet.

A major theme throughout our conversation was how AI is reshaping entire industries faster than many business leaders realize. David explained how travel is moving away from the traditional “search, compare, book” model and toward conversational, agentic experiences powered by AI assistants. But rather than seeing this as a threat, he believes the biggest opportunity for founders lies in combining AI efficiency with deeply human experiences that technology alone cannot replicate.

For startup founders, there are valuable lessons here about positioning, timing, and differentiation. David argued that modern startups increasingly succeed by connecting fragmented ecosystems and reducing friction rather than inventing entirely new categories from scratch. In his view, the companies most likely to win in the AI economy will be those capable of simplifying complexity behind the scenes while creating highly personalized customer experiences at the front end.

We also explored the realities of balancing startup agility inside larger organizations. David spoke candidly about joining HBX Group as an entrepreneur entering a global corporate environment and the tensions that naturally emerge between operational consistency and rapid experimentation. His perspective on how founders and enterprises can work together without suffocating innovation offers some particularly useful insight for anyone navigating partnerships, acquisitions, or scale-up growth phases.

One of the strongest moments in the conversation came when David discussed failure, risk, and founder psychology. He believes too many investors and corporations publicly celebrate innovation while privately punishing failure. Real innovation, he argues, requires giving people room to experiment, fail fast, adapt quickly, and learn without fear. It is a mindset he compares to raising children: creating structure and support while still allowing enough freedom for creativity and growth.

David also shared a piece of advice many early-stage founders need to hear. Looking back, he believes startups often try to scale internationally far too early before securing a dominant position in their home market. The temptation to chase rapid expansion can distract founders from building operational strength, focus, and sustainable foundations.

This episode is packed with practical insight for founders, operators, investors, and anyone building businesses in rapidly evolving industries. From AI disruption and ecosystem thinking to founder resilience and scaling strategy, David offers a refreshingly honest perspective on what it really takes to build companies in an era defined by acceleration and constant change.

What does it take to transform one of the world’s oldest industries using some of the newest technologies available today?

In this episode of Startup Builders and Backers, I sit down with Robin Saluoks, CEO and Co-Founder of eAgronom, to explore how a childhood connection to farming evolved into one of Europe’s fastest-growing climate-tech platforms. Robin shares how building a simple tool for his family farm at just 17 laid the foundation for a business now supporting more than 3,500 farms across 14 countries, helping them improve soil health, reduce emissions, and unlock new revenue streams through carbon credits.

We spend time unpacking why agriculture has remained one of the least digitized industries for so long, and what is finally changing. From AI and satellite monitoring to real-time data collection, Robin explains how technology is beginning to fit into the realities of farm life without adding friction. He also brings clarity to one of the toughest challenges in climate tech today, measuring soil carbon accurately, and why poor data can undermine even the most advanced models.

The conversation also explores the growing role of carbon markets and how farmers can participate without taking on unnecessary complexity or risk. Robin offers a practical view of how regenerative practices can improve profitability over time, why starting small matters, and how trust, local partnerships, and real-world results play a role in driving adoption.

As farming becomes more data-driven, we also touch on the implications for data ownership, control, and the shifting balance of power across the agricultural ecosystem. So as technology reshapes how food is produced and how carbon is managed, are we building systems that truly work for farmers, or simply adding another layer of complexity to an already demanding industry?