Long before Boris Valkov helped build SaaS software to detect lost revenue opportunities, his journey began in his family’s grocery store, where he was answering phone calls. At that time, he was just a kid learning how much a single phone call could matter and how tone, timing, and trust could make or break a sale. This experience stuck with him.
When he became an AI engineer, working for companies like VMware and Meta, he started to look for ways to combine AI with personal touches. At Meta, Valkov helped build PyTorch, the machine learning library now powering everything from self-driving cars to large language models. But even amid the evolution of generative AI and foundation models, something didn’t sit right with him. He realised that there is a massive gap in the industry. Although AI is getting better at simulating intelligence, most businesses still struggle with basics, like what happens when a customer picks up the phone.
From Meta to Missed Revenue
With an aim to combine AI with customer service, Boris left Meta and teamed up with fellow engineer Stanislav Stoyanov in 2021. The pair set out to find a use case where AI could have a real and tangible impact on businesses and help them generate additional revenue. They spoke with over 100 businesses across industries, trying to understand where revenue was leaking.
