Omar Tawakol founded Voicia to capture enterprise voice data that Google and Microsoft don't store. He built a compounding advantage by updating AI models hourly on fresh data, creating a feedback loop that outpaces competitors releasing quarterly updates.
Did we do anything at the early stage to prevent people from copying us? There were so many copycats. Why was I comfortable with that? I had an amazing tech team in a very hard problem space and I knew that nailing the interaction with the customer was so damn hard. And I'll talk a little about that. Here's an interesting story. Before I started voicia, me and the CTO and my co founder who runs product were experimenting with this other idea that I refused to take funding for. We had built an assistant that wasn't a voice assistant. It would read your calendar and your email and it learned very quickly to do things like hey, respond to this email. You forgot it. Hey, this person responds in 30 minutes. You take four days. Don't double cancel this meeting you've already canceled before. Stuff like that. It's a really cool tool. Why didn't I start that company? Because exactly what you're saying. I realized that I would not have a data advantage that Google and Microsoft own each half of the world's email and calendar data. And I as a startup would be competing to get more and more data. And all they had to do is buy crappy competitor number 72 and they could still beat me because it had more data. So I didn't found that company. This company I founded because I realized that 99.99% of all voice in the enterprise is in the ether, not stored in a system of record. So nobody has a data advantage. Literally nobody. So I figured if we had the right algorithms and we created the right user experience, we could get ahead of competitors. And we had a lot of competitors. They didn't scare me. I was worried about. It's actually the same insight behind the folks who started Intuit. When they started Intuit, they said they're not competing with other creators of software for accounting, they're competing with a paper and pencil. So I was competing with people who just took manual notes, not a bunch of startups who were trying to solve a hard problem and didn't necessarily have an advantage. So great question. The other thing we discovered to your question was there is a new type of competitive advantage I didn't think of before. Bluekai had a classic network model, meaning the more data suppliers I had, the more data buyers wanted it, which created liquidity, which made it easier for me to close the next data buyer. And that loop continued. That was a classic network model. This had a new type of network model. I call it a compounding competitive advantage. Because if you could build AI that is constantly training on this data. It's different. Everybody does. AI says their model's concentrating. The hard part is to automate the entire loop of data collection to algorithm creation, to making sure that you haven't created more false positives or changed the profile of how the system works and automatically deploying it every hour. If you could do that, you're competing with other AI companies who will ship new algorithms every quarter. So if you can learn people's language models, so you walk into a meeting and you say a new acronym, the system doesn't know it, and an hour later it knows it, and it updates the language model. It gets better and better, gets stickier for the consumer, and they stay with you and you get more data. So that kind of compounding competitive advantage is really interesting in this new breed of company.
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