The future belongs to agentic AI. I would strongly recommend identifying relevant niches now and starting to deploy AI agents to gain a competitive advantage.

In today’s tech-driven world, artificial intelligence has become a key enabler of business success. But the question remains — how can businesses effectively harness AI to address their unique challenges while staying true to ethical principles?

As a part of this series, we had the pleasure to interview Oleg Baranov.

Oleg Baranov is a serial entrepreneur who has successfully launched and scaled several businesses and startups. These include an internal startup within a software company, where he and his team built a next-generation core banking platform that grew from a team of five to 400 bank installations across CIS countries, as well as an IT professional services firm that scaled from nine people to 1,500 employees serving over 70 major banks. Since 2005, his team has been developing AI- and ML-based solutions for banks, building deep expertise in this domain. In 2023, with the emergence of industrial-grade LLMs, they decided to leverage this experience to create an agentic AI platform.

Q: Thank you so much for joining us in this interview series. Before we dive into our discussion, our readers would love to “get to know you” a bit better. Can you share the most interesting story that happened to you since you started working with artificial intelligence?

One point I would like to emphasize: when we began developing Flametree in 2023, we had heated discussions about whether to specialize in models for a specific business domain or to create a model-agnostic platform. Some advocated for domain-specific fine-tuning, while others favoured a broader, flexible approach. Ultimately, we opted for a model- and industry-agnostic system, which in retrospect appears to have been the right choice. Given the rapid pace of LLM development, building proprietary models is challenging for anyone but the largest players. Being able to leverage multiple models and seamlessly switch between them has become a clear competitive advantage.

Q: You are a successful leader in the AI space. Which three character traits do you think were most instrumental to your success? Can you please share a story or example for each?

This is a complex and multifaceted question, and it’s difficult to address it in full. One principle I strongly believe in is the need to remain a lifelong learner. I personally make a conscious effort to continuously learn and develop new skills, and I actively foster this culture within my organization. Over the past five years, both I and members of my team have participated in programs at leading institutions such as Stanford University, London Business School, Berkeley University, INSEAD, IMD, and others. In a rapidly evolving world, I see continuous learning not as an option, but as a necessity.

Q: Let’s jump to the primary focus of our interview. Can you share a specific example of how you or your organization used AI to solve a major business challenge? What was the problem, and how did AI help address it?

We build a conversational AI platform for banks and customer-centric enterprises working with large retail and SME client bases. We help our customers solve a critical challenge: scaling personalized, high-quality customer engagement while lowering operational costs and improving service accessibility and customer satisfaction.

Q: What are some of the common misconceptions you’ve encountered about using AI in business? How do you address those misconceptions?

Many assume that creating a RAG-based AI agent is straightforward. In practice, delivering an intelligent, personalized AI agent that works effectively at scale is significantly more complex. It requires solving two critical challenges: maintaining continuous, customer-specific context across all interactions, and enabling secure, real-time access to financial and product data. Without these capabilities, AI agents are limited to generic responses and fail to deliver meaningful value. Flametree addresses these challenges by enabling context-aware, data-driven conversational AI agents built specifically for enterprise and banking environments.

Q: In your opinion, what is the most significant way AI can make a positive impact on businesses today?

AI is a vast and multifaceted domain. From our perspective, the area of LLMs and conversational AI agents offers immediate, tangible value. Our project experience demonstrates that deploying conversational AI agents can enhance customer experience and satisfaction at scale, while also optimizing communication costs.

Q: Ok, let’s dive deeper. Based on your experience and research, can you please share “5 Ways AI Can Solve Complex Business Problems”? These can be strategies, insights, or tools that companies can use to make the most of AI in addressing their challenges. If possible, please share examples or stories for each.

I’m not sure AI can solve complex business problems — at least not yet. But it can already automate repetitive tasks and make humans far more efficient at handling non-standard challenges.

Q: How can smaller businesses or startups, with limited budgets, begin to integrate AI into their operations effectively?

Start leveraging services like ChatGPT, Perplexity, or similar tools to improve the efficiency of your employees and business processes and start using platforms like Flametree.ai to build and operate AI agents at scale.

Q: What advice would you give to business leaders who are hesitant to adopt AI because of fear, misconceptions, or lack of understanding?

The future belongs to agentic AI. I would strongly recommend identifying relevant niches now and starting to deploy AI agents to gain a competitive advantage.

Q: In your opinion, how will AI continue to shape the business world over the next 5–10 years? Are there any trends or emerging innovations you’re particularly excited about?

I believe traditional websites and applications will change dramatically. Users will increasingly interact with computers and other devices through voice, while AI agents will become much better at understanding context and behaving in a more relevant and human-like way. Ultimately, they will largely replace or significantly augment the technologies people use today to interact with machines.

Q: How do you think the use of AI to solve business problems influences relationships with customers, employees, and the broader community?

It’s hard to say, as this is not just about technology. Most likely, efficiency in many businesses and services will increase, but at the same time this could lead to some job reductions. The scale of these changes is difficult to estimate.

Q: You are a person of great influence. If you could start a movement that would bring the most amount of good to the most amount of people through AI, what would that be? You never know what your idea can trigger. :-)

I would invest more in education, particularly for children, in mathematics, computer science, and AI. This would give them the opportunity to deeply understand these technologies, rather than just being passive users.

This was great. Thank you so much for the time you spent sharing with us.

Link to the full article on Medium.

Flametree.ai en la EDFC en Ámsterdam

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