EPISODE · Apr 23, 2025 · 53 MIN
Ivan and Olha Pylypchuk: Unlocking the Power of Agentic AI
from Scouting for Growth · host Sabine VdL
On this episode of the Scouting For Growth podcast, Sabine VdL talks to Ivan Pylypchuk, the CEO of Softblues, and Olha Pylypchuk, the company’s COO. In today’s discussion, we’ll explore: What Agentic AI is and why it’s poised to disrupt traditional business processes, how Ivan and Olha are leveraging multi-agent systems to solve domain-specific challenges and deliver business transformation, and the future of AI agents and their role in shaping the workplace of tomorrow. KEY TAKEAWAYS If you talk about traditional AI systems, they can handle one simple, specific task, such as image recognition, data classification, or content generation. Agentic AI is more autonomous and capable of complex decision-making across multiple steps. Our approach is focused on controlled, multi-agent systems. The biggest challenge companies face is collecting and integrating data. Often, companies have their valuable data spread across different systems and departments, like customer databases, email records, and business software. These don’t always talk to each other. To ensure an effective AI implementation, you must ensure that all this data is collected neatly and accurately. Surprisingly, some companies don’t know how their people work. When you observe their processes, you sometimes see that they miss important details about their daily operations, which can lead to significant wasted investment when we rectify these mistakes afterwards. That’s why we invest a lot of time working with and talking to the businesses about how their workflows move from point A to B. Then, we can enhance them with AI. How team members embrace this technology is very important. Even a perfect solution will fail if teams don’t use it. We create simple interfaces and make sure our systems explain their recommendations in plain language. This approach dramatically improves understanding of how AI works and builds trust. BEST MOMENTS ‘Agentic AI gives us scalability in different domains, explainability to understand what it’s doing, so we can provide the exact information that is needed across an organisation.’ ‘It’s important to start very small, on a piece of a project, so the AI can show clearly its quick results. After the goal has been demonstrated, then we scale the solution.’ ‘Our recruitment solution helps reduce time to hire by 60% and provides an increase in the quality of hires by 40%.’ ‘It gives you more time to do strategic work that brings more value to the business than managing this data.’ ABOUT THE GUEST Ivan Pylypchuk is the CEO and AI Solution Architect at Softblues, a company specializing in building multi-agent AI systems to tackle real-world business challenges. LinkedIn Olha Pylypchuk is the Co-founder and Chief Operating Officer of Softblues, where she drives operational excellence and spearheads AI-driven business automation initiatives. LinkedIn ABOUT THE HOST Sabine VanderLinden is a corporate strategist turned entrepreneur and the CEO of Alchemy Crew Ventures. She leads venture-client labs that help Fortune 500 companies adopt and scale cutting-edge technologies from global tech ventures. A builder of accelerators, investor, and co-editor of the bestseller The INSURTECH Book, Sabine is known for asking the uncomfortable questions—about AI governance, risk, and trust. On Scouting for Growth, she decodes how real growth happens—where capital, collaboration, and courage meet. If this episode sparked your thinking, follow Sabine VanderLinden on LinkedIn, Twitter, and Instagram for more insights. And if you’re interested in sponsoring the podcast, reach out to the team at [email protected]
What this episode covers
On this episode of Scouting For Growth, Sabine VdL speaks with Ivan Pylypchuk, CEO of Softblues, and Olha Pylypchuk, the company’s COO, to unpack what many leaders are sensing but struggling to operationalise: Agentic AI isn’t a feature upgrade. It’s a new operating model. Together, they explore what agentic AI really is, why multi-agent systems are poised to disrupt traditional business processes, and what it takes to deploy AI agents that teams actually trust and use. Agentic AI: from “single task” to autonomous execution Ivan breaks down the difference clearly. Traditional AI systems typically handle one narrow task: image recognition, classification, or content generation. Agentic AI goes further. It can manage multi-step decision-making, coordinate actions, and operate with higher autonomy—especially when designed as controlled multi-agent systems, where each agent has a defined role and guardrails. In other words: not just intelligence… agency. The real blocker isn’t AI — it’s data fragmentation Softblues sees one challenge again and again: companies have valuable data spread across disconnected systems—CRMs, email, customer databases, business tools. And when those systems don’t talk to each other, AI can’t deliver reliable outcomes. Their message is simple: for AI to work, data must be collected neatly, accurately, and integrated across the organisation. Without that foundation, even the best model will produce weak results. The hidden issue: companies often don’t understand their own workflows One of the most striking insights from Ivan and Olha is that many organisations don’t actually know how work gets done day-to-day. When they observe real processes, they often find missing steps, informal workarounds, and operational blind spots—details leadership didn’t realise existed. That matters because implementing AI on top of an unclear process can lead to wasted investment later. Softblues addresses this by spending serious time mapping workflows from Point A to Point B, then enhancing them with AI rather than forcing automation into chaos. Adoption wins or loses everything Ivan and Olha emphasise that even a “perfect” AI solution fails if teams don’t use it. That’s why they focus on: simple interfaces recommendations explained in plain language and explainability that builds trust quickly Agentic AI only scales when humans feel confident in what it’s doing—and why. Start small. Prove value. Then scale. Their deployment philosophy is practical: start with a small part of the project where AI can show fast results. Once value is proven, scale confidently. It’s how organisations move from experimentation to transformation without breaking operations—or trust. Real outcomes: speed + quality Softblues shares measurable impact from their solutions, including: reducing time-to-hire by 60% increasing quality of hires by 40% The bigger payoff, though, is strategic: freeing teams from data wrangling so they can focus on higher-value work that moves the business forward. Why this episode matters For enterprise leaders in insurance and financial services, this episode is a blueprint for agentic AI adoption that’s grounded in reality: agentic AI thrives in controlled multi-agent systems data integration is non-negotiable workflow clarity comes before automation trust and usability drive adoption small wins create scalable momentum Because the future of work won’t be shaped by AI that’s impressive in demos. It will be shaped by AI agents that quietly make organisations faster, smarter, and more strategic—every single day.
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Ivan and Olha Pylypchuk: Unlocking the Power of Agentic AI
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