Outset raises $30M Series B to scale AI-moderated research for Fortune 500 companies

service. It's a vacation home, but better, and you can get there in your self-driving car. Our next guest is Aaron Cannon.

That is a powerful name.

That's a powerful name.

Scrub Capital Scrub Capital.

They saw him and they were like, "Put the capital. Put the capital in the cannon. Launch the capital cannon at Aaron Cannon. Welcome to the show. How you doing?

Thank you. Thank you.

And look at that chart in the background.

What cheeky little chart,

guys? That's real numbers. That's actually That's the real data.

Real data.

Hit it again. Hit it again a few times. [snorts]

There we go. We're fired up, Aaron Cannon. We're happy to have you on the show. Uh, thank you. Would love would love an introduction uh on yourself and the company.

Yeah, I'm Aaron. I'm the CEO and co-founder of Outset. Uh, I was on your show. I think it was at YC demo day like six months ago.

That's right. That's right. We were super bullish on you.

That's awesome. No wonder you're back.

Thank you.

No wonder you're back.

Yeah, I had my my yellow ramp hat on in the YC offices and I was I was sharing our series A.

Wait. Yeah. So, so break it down for people because they're going to assume you were in the in a batch this year, but you you you went through uh in 2022, was it?

Yeah, we're we were 2023, summer 23. We went through YC batch

um and been growing since then. I just happened to be in the office and we raised our series A at the at the YC demo day, so I popped in. Um and yeah, so so uh outset is uh AI moderated research. So if you've ever tried to, you know, understand your customers or something, it's it really sucks today or or in the past. And uh finally, it doesn't suck. I mean, basically, you know, surveys are the old school way to do it. Um or you talk to users one by one and you know, talk to maybe a dozen or so and and now AI does it for you. So our uh that's what our platform does. And we um we just raised our series B uh announced it yesterday from Radical Ventures. There it is. Um and uh yes uh it's been great. So, uh, here we are six months later.

Did you ever was Paul Graham ever concerned about outset? Was he worried, you know, founders might stop talking to their customers or is he comfortable with the AI talking to the customer on their behalf?

You know, I didn't clear this with with PG personally, but uh,

dude, you got to clear it with you got to clear it with PG. You got to get his blessing. You got to get his blessing.

I I I did not do that, but uh, it's part of the reason we don't work as much with startups and and we work with Microsoft, Google, folks like that. um, Weight Watchers and Nestle and so so we go for the big enterprises.

What do what does, uh, what does success look like when when you're working with these companies? What are you pushing towards? Is it a key insight that impacts a a future product decision? You know, what does actually winning look like?

Yeah. Yeah. It's it's uh it generally falls into two things. like either they're doing product research where it's about a key insight that drives a product decision of what to build or even like not to build. There's like a famous uh Airbnb uh Brian Chesky told the story of like there was like a a million dollar yeah re research saved the millions of dollars because of like one bad design, right? And so like you know it could be a massive like a single insight can be hugely differentiating for a product. Um and then there's marketing where you're saying like I'm about to you know release a new product to a new market. you know, you're Nestle and you're testing new concepts. Um, you got to get that right. Right. So, that's that looks like making smarter decisions and making them really really fast. And that's like the real thing is that now with us, you can actually gather, you know, hundreds of actual interviews like indepth nuance like really hear from people and you can do that in a couple of hours and then we synthesize all that data so you can go make a decision. Are you guys taking away jobs from researchers or are researchers just able to do far more work and get far more insight?

The the the classic AI question of uh yeah it's it so the reality

yeah it just feels like yeah I mean if you look in engineering organizations people are like my engineers are much more effective I'm going to make I'm going to build a lot more product. I want more great engineers. In this case, I I I don't have a lot of insight into how research teams at some of these big companies work, but I could see them saying, "Hey, we historically needed to hire

this outside firm to conduct this research or and we needed x number of people to kind of manage it and try to unpack what was actually happening."

A lot of them might also have just been using web forms, right?

Yeah.

Yeah. So, okay. So, so what we actually see on the ground is very much not the uh get rid of your researchers. Quite the opposite. And I think the the the reason for that is there is like there is there isn't a ceiling of like I don't need any more insight on a thing right there's actually kind of it's like an insatiable demand for it. The problem is the old way was not economical. So you would have you know your researchers you know they do one study every month or two and it would be you know like talking to to to 15 users and now that one researcher can actually do a study every week each time talking to 200 users. And so you basically are like making smarter decisions. And then you add the speed at which people are putting new products into the world, you actually need that insight faster, right?

And so what we see on the ground is basically a research team adopting it and saying, "Holy crap, like I can actually go like do twice as much or go twice as fast um with, you know, the same people we have on the team today.

How multimodal are you today? How multimodal do you want to be in a few years?" I can imagine uh research is happening you know on video interviews, audio, textbased interviews, web forms like what are you doing today and then what do you want to do?

All we we want to do all the modes all the modals um no so so today we are video audio text and then you can do kind of forums you know think like classic survey questions

radio buttons and radio buttons.

So do you just email or text a customer and say may I research you? Yeah. [laughter]

Yeah. That's exactly it. That that's the language. May I research you?

Um, no, but but then but then we also do screen sharing.

So that's actually where you're getting a a participant to video, audio, radio buttons, and then also share their screen while they're interacting with your prototype. Um, so you kind of do all of that together and then we partner with a bunch of a bunch of uh panels that I call them to to help kind of source people, right? So in our platform, we can actually source from, you know, millions of people. And are you building like the full customer experience management platform down to uh data collection but then also analysis because it sounds like you're adding sourcing but it's not like you're you're going to give me a big bag of text and then I got to go sort it out elsewhere.

Yeah. The the theory's always been like the the if we're going to help you scale and speed up the way you collect the data, we got to break it down for you afterwards, right? And it's just two sides of the same coin. So since day one we've had these two sides right our core platform AI moderated research is like collect the data synthesize the data tell you what matters the thing we now are building into the future and the reason we raised a bunch of this money you know just 6 months later is like we're going from think like you know study by study I got a question let me go answer it to the always on customer intelligence platform right the the experience management where you know at every touch point you know you get off a flight you get a oh how was your flight or you you know you you you get a posturch purchase feedback form and really every point in the journey, right, should actually be conversational insight, should be continuous. We should have contextual questions that actually make sense. And so pulling all that together.

Mhm.

Makes a lot of sense.

I have one I sorry I have one more. Uh fraud detection like what does that look like? Um and yeah, like like is that is that AI powered or AI enabled or is that just like best practices? like what what is the bad like how big of a problem is fraud in customer research?

Yeah. If you talk to anybody in the in the industry, they'll say like it's a big it's a problem like and Chad GPT made it worse, right? Yeah. Um so the answer

is that what is that

because I get paid $100 to tell Microsoft or get a gift card to tell Microsoft how I'm using Microsoft Excel and I'm like well if I just go to Chad GBT and I'm like how am I using Excel? It'll just make something up and then I just copy paste that in and then I get the $100 Starbucks gift card. Is that roughly correct?

Yeah, that's that's right. But but what happens is like on surveys it's really bad, right? Because you have an open a free text field and you just paste it in.

You're just detecting whatever. Yeah.

Right. Well, like luckily we're because most of our customers are doing very like video based stuff. It is much more right that that is harder to like uh uh you know fake your way through. Um but we built our own fraud detection agent, right? And it's like it's actually kind of fun to watch cuz it's basically looking at your screener answers like oh you said you were an expert in you know Python and then like later in the interview as they interviewed about you know what tools you're using it's like they don't know anything about it and then you get your you know as a customer you get your reasoning so that the AI agent tells you oh this this guy does not know what he's talking about [laughter] and so it's uh pretty impressive. Yeah

it's fantastic. Well thank you so much for taking the time to come on the show. Did we hit the gong already?

Hit it again.

I'll hit it again.

We did. Yeah. Hit it one more. I'll be back.

$30 million series. I I don't know if we actually got to the number. $30 million series. Radical Ventures.

Hey, push yourself and the team. Come back in Q1. [snorts] It's not all about fundraising, but it is a pretty good indicator of momentum.

Call up Rob Taves at Radical Ventures. Say, "Give me another 30. Give me another 300."

How about Yeah. How about you put your money where your mouth is, Rob? Make a bet. Take a bet on us.

Yeah. Look at the graph. Look at the graph. Well, thank you so much for coming on the show again. Have a good one. We'll talk to you soon. Goodbye.

Uh before we bring in our next guest, we have some breaking news. Broadcom has smashed earnings. Earnings per share of 195 versus 172 projected revenue of 18 billion. People were projecting 18 17 12. Look at this AI image of a crying bear relative to AVG. Oh, cocktail.

Bears in shambles.

The simp private equity has done it again. up 3% after the lowjack riding the green line up

uh and that is uh fantastic news for the