[Podcast] A day in the life of an AI company founder

Where AI meets leadership

What does it take to lead an AI company? In this episode of AI at Scale podcast, we sit down with Katya Lainé—CoFounder & CEO of TALKR.ai, President of the AI Commission at Numeum, CoFounder and VicePresident of Le Voice Lab, and CoFounder of OpenLLM France—to get a unique glimpse into the daily life of an AI company founder. 

Katya takes us on a journey through the realities of building high-impact AI solutions long before GenAI was part of everyday business vocabulary. She shares how TALKR.ai pioneered multilingual conversational AI at a time when the ecosystem was immature, the data scarce, and the technology still evolving. She also explains what it now means to scale AI that carries the weight of customer expectations 24/7. 

Through stories of frustration, innovation, and leadership across multiple organizations, Katya reveals the creative problem-solving that defines her role—always with a strong focus on ethics and deep customer understanding. 

For any leader navigating business strategy and AI implementation, this conversation offers rare clarity on what truly drives AI success inside enterprises: being prepared to change processes and ways of working. 

What will the future demand from those at the forefront? 

Learn from this conversation. 

What you will learn:

• How AI companies can innovate when data, tools, and ecosystems are limited 
• How leaders balance product, ethics, and execution in customer‑facing AI 
• What an AI founder’s day really looks like behind the scenes 
• How voice‑AI transforms customer journeys and internal processes 
• What skills and mindsets future AI leaders must build now 

Listen to the AI at Scale podcast 

Listen to Katya Lainé: A day in the life of an AI company founder episode. Subscribe to the show on the preferred streaming platform (Apple Podcasts, Spotify).

Transcript

What inspired Katya to create her company ? 

Gosia Gorska: Welcome everyone. This is the AI at Scale podcast by Schneider Electric. My name is Gosia Górska and I am the host of this program. Today I have the pleasure of welcoming Katya Lainé. Welcome, Katya. 

Katya Lainé: Hi Gosia. It is nice to be with you. 

Gosia: Nice to have you. Katya is the co-founder and CEO of TALKR.ai, a company that is reshaping how customers interact with businesses today. For nearly a decade, Katya has been at the forefront of offering intelligent voice assistants, helping businesses deliver 24/7 customer engagement. She is a multi-founder at heart because not only did she found TALKR.ai, but also the Open LLM France initiative, which is dedicated to promoting open-source, ethical standards, and transparency in AI development. 

She is also the co-founder and Vice President of Le Voice Lab, advancing voice and language technology. Katya also serves on the board of Numeum as president of its AI commission, actively championing responsible and high-impact AI adoption. She holds an MBA and a master’s in broadcast journalism. Katya, my first question is: what inspired you to create TALKR.ai? Can you share the moment that sparked this initiative? 

Katya: It was born from frustration. I started my company with my co-founder and partner 14 years ago. We began by building tools for mid-market companies to allow them access to technology. Back in 2010 and 2011, there was an explosion of digital technology, but small and mid-market companies did not have accessible or free access to it. We started building no-code tools, and we saw that when a company interacts with its customers, there is always a wall between them. 

We noticed days going by without any interaction. Companies had live chat propositions, but we wanted to provide an immediate answer so the customer felt heard and knew the company was taking charge. Back in 2014, we started thinking about automated tools like chatbots. That business need and frustration sparked the idea. 

Challenges before GenAI 

Gosia: That is super interesting. I am curious to hear about your experiences as a founder because when you started, it was prior to GenAI. I guess you were facing the challenges and hurdles of a very early stage of AI as well. How did you overcome them? 

Katya: As I said, back then there was AI, but we struggled with similar things to today, such as a lack of data. For voice conversation, we did not have any data; everything is private. When working with companies, it is very difficult to get access. We had to anonymize all conversations to build big data sets, clean them, and structure them. 

We also faced challenges with algorithms. In 2015 and 2016, when we built a virtual assistant over the phone in French, all the technological bricks were based mostly on the English language. Solutions for French existed but were not very effective. We had to build our own algorithms and our own NLP and NLU engines. We struggled with the technical aspects, but it was also very new, so we had to go through a period of early adoption and innovation. 

The third challenge, which is still relevant today, is about transformation. We are a B2B2C company—serving a company but also serving that company’s customers. The transformation inside a company is very slow and difficult. You have to be very careful with what you are doing because your tool is transforming how the work is done, how the company interacts with customers, and how teams interact internally. Those were the three main challenges we faced back then, and they remain similar now. 

TALKR.ai solutions 

Gosia: It started with frustration, then you spent time organizing the technology to find a solution and propose value to customers. Tell us a bit more about what the company is doing and what kind of solutions you are providing. 

Katya: TALKR.ai has two major components. First, a no-code platform that enables companies to easily build and manage virtual assistants for various use cases, such as healthcare or retail. This virtual assistant can pick up the phone 24/7, have a natural language conversation, and solve customer inquiries in real-time. 

TALKR acts across the entire customer journey: marketing, sales, support, and customer service. We can automate tasks in all these areas. For marketing, we can better qualify customer needs. We can call them with a virtual assistant—not cold calling, which is difficult, but asking questions to propose an adequate offer or schedule an appointment with a seller. I talk about calls because doing calls is much more difficult than chatting. Everyone knows chatbots, but having a natural voice conversation over the phone is much harder. 

Gosia: Can you go into more detail? I am curious about the types of companies using your solutions and specific use cases. 

Katya: We help companies pick up the phone 24/7 in retail, IT support, storage, and logistics. For example, for a storage company, we changed 16 processes across 28 agencies. Now, when customers call the company 24/7, a virtual agent assists them. If they are calling for an invoice, we send it automatically without transferring the call. 

If a customer is blocked in front of their storage box at 11:00 p.m., the virtual assistant has a conversation to authenticate the customer via the CRM connection. If we see the customer hasn’t paid, we propose a payment process in real-time. By the end of the process, the customer can access their box. We assist them from A to Z, making the process self-served. 

This helps the company serve customers 24/7 and automate about 67% of processes. During working hours, we transfer questions requiring more support to the staff. Ultimately, customer satisfaction rises by 45%, and the company becomes more efficient. Another example is outbound calls for logistics. When delivering products, we call customers to validate if they are home. Based on this validation, the company can schedule the delivery. This impacts not only interaction but also internal process optimization by 35% to 45%. In general, we can solve 32% to 92% of all customer inquiries in real-time without human interaction. 

Ethical and trustworthy AI 

Gosia: I know that one of your interests is ethical and trustworthy AI. Do you have any examples where you had to solve challenges around trustworthiness so the customer can actually trust the solution? 

Katya: I have been working on ethical topics since 2018. The most interesting thing about ethics is that it is practical, not theoretical. At Numeum, we build tools to help the ecosystem guide companies in their real processes for building AI solutions. Developers often don’t know what AI ethics means; we have to train them on how to work with data. Everyone in the company has a role to play in managing data and customer interaction. 

Beyond this, the most difficult aspect was bias. Our society is based on bias, and company data is biased. When companies started training solutions, some were racist or promoted men more than women. We realized we had to pay close attention to this. That was the turning point for me. 

A day in the life of an AI company founder 

Gosia: I think this can be very interesting to our audience. Could you describe a day in the life of an AI founder? What activities take most of your time? 

Katya: I wear many hats. Today, for example, starts with this interview, which sparks my day. Then I check my emails and have client meetings. I also meet my team to think about our R&D for the next two years and follow up on projects going live right now to check the results. I also meet with my accountant. It is challenging because I have so many different roles. 

Gosia: You have had a fascinating career, transitioning from journalism to AI. Can you tell us more about your journey and if it changed how you approach business? 

Katya: I think it is very natural. I started in journalism and liked it very much. Journalists are trained to understand everything happening in the world. I also came from a very business-oriented family, so I knew I wanted to do business eventually. 

I am very proactive; if I see something, I want to change it and have an impact. Journalism and communication are about conversation, understanding people, and being in touch with them. Business with customers is also about understanding and trying to help them. For me, I am doing the same thing but differently—helping people and having a business impact at scale. 

Role at Numeum and advice for leaders in tech and AI space 

Gosia: Indeed, you mentioned you are proactive. That is why you are not only the founder of one company but also the co-founder of other organizations. You mentioned Numeum several times. For those who don’t know, this is the organization of digital companies in France representing platform players, software publishers, and digital service providers. Can you tell us more about your role there? 

Katya: At Numeum, I am an elected board member. We are active and help the ecosystem by building social and technological tools. We work with our peers to define the future of technology—not just AI, but also quantum computing, open source, and cybersecurity, which is at the heart of what we are developing. 

Gosia: My last question is about advice. What would you advise people who are preparing to lead companies in the tech and AI space? Do you have any success criteria that worked for you? 

Katya: Jump into the AI accelerator because it is going to get faster and faster. It is transforming dramatically—not only the way we work but also the way we live. We need people with an understanding of the world, not just technology. AI has reached a point where we need people with real business understanding. 

Prepare yourselves. I think for the next 3 to 5 years, we are going to see a transformation in competence. We will see changes, and we have to be very careful about how our companies prepare employees for this transformation in how we work. 

Wrap up 

Gosia: Thank you so much, Katya. It was great hosting you today. 

Katya: Thank you very much, Gosia. Have a nice day. 

Gosia: Thanks. And to everyone listening, thank you so much for joining us. This was the AI at Scale podcast. Be sure to subscribe to our podcast on your favorite platform and discover the next episodes. Thank you. 

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