Editor in Chief Sarah Wheeler sat down with Diane Yu, co-founder and CEO of TidalWave, to talk about the benefits of building an AI-first company in today’s business environment.
Yu founded and sold ad tech platform FreeWheel to Comcast in 2014, and she served as chief technology officer at Better.com from 2021-2022.
This interview has been edited for length and clarity.
Sarah Wheeler: What’s the advantage to building a company from the ground up as AI-first?
Diane Yu: It’s very fortunate that we started TidalWave at the right time — where the tech model for digitization in the industry just started to pick up and at the same time, generative AI really came to the surface. As a technologist and as an engineer, I have been following that trend for a long time and then realized this could be the very last piece of the puzzle.
Now we can build something unique from scratch — an AI-powered co-pilot engine — without the burden others have of legacy software they have to adapt to. We were able to move so fast and so quick that coming out of stealth we were able to get approved for integration from Fannie Mae and Freddie Mac.
SW: What differentiates your technology?
DY: In order to apply generative AI to the mortgage industry, it has to be 100% accurate — no hallucinating. And this is the reason why we chose to purposely build an AI engine, not using any type of ChatGPT wrapper. A lot of companies are saying they have something similar, but they were building a wrapper, and that wouldn’t work, because there’s no way you can stop the hallucinating problem. So, that’s No. 1. We chose a harder path, but eventually we will come out winning, because we purposely built a co-pilot engine.
No. 2, it has to be transparent — I typically say it’s a white box. I also use the terminology of a reasoning traceability. That’s a key criteria for us, because you have to make sure it’s super clear to all of those lenders how you come to the conclusion, how you create the reasoning based on your interaction with the borrower, so that lenders can go back and trace back 100% how everything’s being evaluated based on their standard.
The last thing that differentiates our technology is how we protect consumers’ personal financial data. Many companies, when they say they are utilizing generative AI, OK, if they send consumers’ personal financial data out to OpenAI, that’s not going to work. That’s why we purposely built our own library and our decision engine so that we can safeguard that information, and then prevent any type of leakage by utilizing a generated AI portion out there.
SW: How are you leveraging AI differently than some legacy companies?
DY: Our AI co-pilot Solo is working with the consumer via the conversation, interacting with the consumer, so that we understand the purpose of the consumer interaction and also get permission to access their data. When the consumer allows us to have access to their information — as an example, for the credit report — we would use our AI engine in the background to evaluate the individual’s credit report data.
We would identify the items from their credit report data that require further information based on the underwriting pipeline. So, we would ask the consumer to provide those additional documents, knowing that once the consumer started a mortgage application an underwriter will have to ask those questions anyway. We’re also calculating everything, like their income, and we’re also gaining permission to access their financial information about their income.
That’s the big difference compared to a lot of legacy lender technology, which just collects documents to send off to different departments. We use our AI capability to interact with the consumer already, so once it gets to the underwriting department of our customers, they can review and check, check, check — everything’s good.
SW: How does TidalWave fit into the next iteration of the mortgage industry where there are fewer people?
DY: Lenders have already cut to the bone, and they’re still losing money. And when the interest rate comes around, when volume comes back, the lenders have two choices. One is to hire all those people as quickly as possible and bring them back, and then train them on the process that people aren’t familiar with. So, you originate with a lot of problems, a lot of errors.
Or you’re utilizing a new capability and helping your existing staff members be a lot more productive — they can just focus on things that they’re so specialized in and so good at doing. And then you can handle the volume when it’s low, and you can chase the additional volume when it comes back.
SW: How do you think about security?
DY: Coming from the background of building a technology platform, and then at FreeWheel, my first company, the type of company utilizing FreeWheel’s technology is a company like NBC and CNN, global media companies. So, we understand 100% how important it is for the platform to be highly secure.
We take the same approach at TidalWave, because we understand that bringing on customers that handle personal financial data, it could make or break a company if you do it wrong. So, we pay attention to the security from day one. As an example, even at this stage, we encrypt everything so that you don’t have to worry about being hacked and then having consumers’ information being leaked out.
SW: What keeps you up at night?
DY: My worry is that volume is going to come back and a lot of lenders will have no choice but to run out and hire a lot of people, and basically go through that nightmare of the industry again of hire/fire. So, as a small startup, we’ve run super fast because we want to make sure that we can help as many lenders as possible so that they don’t have to go through this nightmare.
SW: What does your team look like?
DY: We are a team of 15 and growing. Half of the folks are in New York, so we come to the office like four days a week. And for a small startup, I have to say that face to face is so important, especially because we’re evolving so quickly.
This is my second company and I am so fortunate, especially from an engineering talent perspective. I’ve been able to bring the best team with me. My core co-founding team are the ones who built the first company with me from scratch. They followed me into my time at Better and then followed me out of Better, so that team has the benefit of working with each other for, like, 15 to 20 years.
And then the other half of the team is the members that I had the opportunity to get to know during my Better days. I also have people with 20-plus years of mortgage origination and loan officer experience working with us. The benefit of a small team with the right level of expertise is that we’re working together for the same common goal.
SW: As a startup, how do you deal with the pace of change, especially in AI?
DY: You need to make sure you focus on what you specialize in. So, we focus on underwriting, and we fully focus on the mortgage origination knowledge that we know no one else will be out there building. Now we see a lot of companies building multiple large language models, which is a good thing, because we can utilize all of them, and then whichever one is the winner, we’ll do a deeper integration with them.
I think of that famous quote about software eating the world, and now AI is eating software. And we truly see that right in front of us. Using AI capability, it can gradually take away, piece by piece, all the existing legacy software capabilities.
