We founded Opti Solutions just under a year ago, shortly before our wedding. Neither of us is a developer. We both come from marketing and sales, where we each had our own work before.
In the first episode of the podcast we went through how that turned into a team and what we actually do in practice. Below is a summary of the conversation.
From microbiology and fitness to B2B
Žan has a degree in kinesiology. For seven or eight years he coached athletes in powerlifting and weightlifting; with two colleagues he opened a coaching business and later a gym at Dolgi most in Ljubljana. His role was always marketing and sales, which led him to freelance work and to a fractional CMO role for an American company.
Nuša has a degree in microbiology. During her studies she worked in a laboratory and realised it was not for her. She started selling digital products on productivity and organisation; that grew into coaching, and coaching grew into the agency Easy Busy, where she ran Meta ads, email marketing and funnels for companies.
When the wave of artificial intelligence arrived, it fitted neatly with what we were already doing. Marketing and sales involve a huge amount of manual work that can be automated even with simple tools, without AI. Add some basic artificial intelligence on top and the value goes up quickly, while the barrier to entry comes down.
The first client came from our phone contacts
We read a book about AI agencies and got from it the idea of what kind of offer to take to companies. Then we started calling. Everyone we knew, and everyone in our contacts. We got to good companies quite quickly.
Time-wise it was awful. We got married and went on honeymoon, while each of us still had our own business that kept running. Mixing the old and the new was the hardest part. Nuša put hers aside sooner, Žan gradually; today we are both here full time.
The reason was simple. The working day was not eight hours but ten, twelve or fourteen, plus things in the evening and at weekends. You cannot run two businesses like that.
What we actually do
Companies today know they need AI. What they lack is the how. They do not have the knowledge, and often not the time or energy either, because they are drowning in work. And that work is exactly what AI could take off their desk.
That is why we always start with a diagnostic review, where we look together with the company at where artificial intelligence would have the biggest effect. In some places that is time saved, in others revenue they are currently losing. Only then do we talk about what gets built.
In concrete terms it is things like: a chatbot on the website, searching through emails and writing new ones, meeting notes that a person no longer writes, preparing quotes, pro forma invoices and contracts, automatic follow-up after a quote is sent, and automatic replies to new enquiries.
Twenty hours in half an hour
At one company, an employee spent two to three days on a single presentation for the foreign parent company. We showed him how to use Claude and the integrations he already had to help with it. When we came back a few days later, he told us he had done the same thing in half an hour.
That is not an exception. After the basic tools are in place, companies report within a few days that they save between 30 and 50% of their time. The tools are often not complicated at all, but the effect is large.
The goal is not layoffs
In no project so far has the goal been for the company to let someone go. The goal is higher productivity and taking load off the team.
An employee who knows how to use AI in their work is not more at risk but less, because they are worth more to the company. Human oversight is still needed everywhere, and there is no way around it. But if that person achieves three or five times the output, that is a plus for them and for the company.
More AI, more personal contact
In the diagnostic review we always ask employees what they would do if they had more time. They often answer that they would spend more time with clients and go to more meetings in person.
Companies that introduce artificial intelligence well will therefore end up with more personal contact with people, not less. Which is exactly the opposite of what they most often fear.
What to take away
In the first year we helped more than 50 companies and entrepreneurs, with annual turnover from one million to 15 million EUR. What proved most constant was not the technology but the order: first understand where the company loses time, and only then choose the tool.
Companies do not fall behind because they do not know they need AI. They fall behind because they are drowning in work and have no time to work out where it would help them most.