Short answer: Rob Williams says Read AI's narrow focus is the information worker whose work happens in meetings, in any industry. An early use case was time-shifting context between offices, such as African oil fields and Asian offices.
Watch this answer from Episode 54 (starts at 10:00) · Episode 54 notes and transcript
From Episode 54: Nobody Takes Notes Anymore. 5 Million People Let AI Do It Instead., starting at 10:00.
Jordan Metzner [10:00]: Yeah. I think on CNBC today, somebody mentioned that, like, the opportunity for EAs to move into, like, project management based roles since, like, they're so good at kind of multitasking kind of opportunity there. 5,000,000, again, that's a huge number. Has... Have you found success in certain industries or regions or, focuses like, hey, we're really good with tech companies or really good in life sciences or kinda, where have you guys found the niche or small businesses or whatever wherever kind of has been, a good place for you guys.
Rob Williams [10:31]: This is one of the conversations years ago when we were raising our series a. We had these conversations with existing investors, with prospective investors, and the traditional lean startup advice is pick a narrow focus, nail that narrow focus, and don't think about anything else beyond that. I agree and I disagree with that. We took the approach that actually the narrow focus here, it may sound like we're avoiding focus, but the narrow focus is the information worker. And these people who go about their days and their work happens in meetings, those are the people we care about. And so whether you're in meetings because you're a project manager or an accountant or consultant of any variety, it doesn't really matter what the content is. What matters is the structure of your day, the importance of continuity in your relationships, of continuity in your context, and so that's what we went after. And from a market or a segmentation or industry perspective, I've learned about industries that I frankly would have never thought about when we started the company five years ago. And so we have, for example, oil fields in Africa working as subsidiaries with companies with offices in Asia, and one of the biggest use cases for us early on was time shifting context between different offices within a company. And so that's a how do we mobilize information without making people get up in the middle of the night to attend calls scenario.
Rob Williams [11:59]: And it really doesn't matter. They could be making, any kind of widget and they'd still have the same problem across time zones. So, that's been the approach we took.
Jordan Metzner [12:07]: Ryz Labs builds production grade AI for the world's most ambitious companies. Support engineers. Data scientists. AI architects. All working together on your problem.
