Parallel Web Systems raises $100M Series A to power AI agents doing real-time web research at scale

Speaker 4: I am.

Speaker 1: Oh, yeah.

Speaker 12: You got

Speaker 1: the step of behind you. Cerebral Pepro AI Summit. Congratulations. What'd you announce on stage? What are you announcing here on TVPN?

Speaker 4: I announced on stage that we just raised series a. We raised a $100,000,000 from some of the best investors. Yeah.

Speaker 2: Let's give it up for the best investors. 740,000,000. Index ventures. There we go.

Speaker 1: Got some spark capital participation. We love to see it. Coastal is in there first round. Terade, wow. Really? Really? Murderers row. Mamoun Ekaliner is joining the board. That's exciting. That's exciting.

Speaker 2: What? Kinda looking like the Figma Yeah. Figma board.

Speaker 1: We got a we got a good crew here. I like this. Yeah. So so so take me through take me through the actual company progress, the progress that unlocked this $100,000,000 series a. Obviously, there was some demand. There was some research progress. What was the shape of the data points that went into the ultimate deck that got this across the finish lines?

Speaker 4: So with our first time two years ago, we started with this sort of pie in the sky idea that agents are gonna use the web, and they're gonna use them a lot. Yeah. And we need to build new infrastructure for them.

Speaker 1: Yeah.

Speaker 4: There weren't any agents around in that moment. Right? None of them was using the web when we started.

Speaker 2: Were trying. Some of them were trying.

Speaker 4: Yes. And this year, like, everything's changed. Like, everyone's now building an agent

Speaker 1: Mhmm.

Speaker 4: And every agent wants to connect with those. So the market just came alive, I wanna say, nine months ago. The most, like, frontier customers started doing its last years Mhmm. And became our design partners. This year, the number of customers, the number of queries, the diversity of work, like, there's quoting agents using us. Yeah. There's people in sales, building agents using us, finance, risk, compliance, insurance, health care, people doing scientific research agents

Speaker 1: Yeah.

Speaker 4: People in pharma and biotech, figuring out how to use web search APIs to build agents. So, like, it's completely different world this year as it relates to agents agents using the web.

Speaker 2: So, yeah, to to make it super simple, people are using parallel web systems within, you know, maybe a SaaS provider is integrating parallel into their products so that if somebody's doing research, let's say, a CRM on a customer, you guys can help, you know, them use agents to do a web search and, fill fill in that CRM with data. That would be one example.

Speaker 4: That is a perfect example. You see this white ostment. Our products are APIs. Our users are agents. Our customers are people building agents. Right? So if someone builds an agent to say, okay. I'm going to take your CRM and add very interesting data to it so that you can take better actions. Mhmm. That agent, the data, will call our APIs in order to search the web, in order to pull content from the web, in order to get the highest quality information to be able to fill up that database.

Speaker 1: React to this post from Jim Kramer. He says, when I use ChatGPT or the others, I can tell quickly that they won't pay up for good sources. We all know this. So what's the point? They need to start paying newspapers and stop using bogus sources we would never use ourselves. We need integrity, not volume. There's a bunch of ways you could read that, but my take was there is a data quality opportunity, especially in the enterprise, especially where willingness to pay is maybe really high. And so how are you thinking about, making sure that Parallel and the deep research API has the highest quality data forever?

Speaker 9: I perhaps,

Speaker 4: I've been partly is it Jim Kramer? Mhmm. I don't always. The so there are two things there. How do you get the highest quality DP search results? Mhmm. That is a lot of things. High quality data, authoritative data is a part of it. Mhmm. And then there's a lot of other technology we're building on top, whether it be at the ranking layer, the retrieval layer, the crawling layer, the reasoning layer Mhmm. To get you higher quality PCGs. I I ask you to try our deep research product and compare it to OpenAI's, and we win nine times out of 10. Mhmm. So I want everyone to try that and tell us if I'm wrong. So go to the data question. I think there are deals being done by people. The the world I don't wanna live in is only Google and OpenAI's agents have access to some data. And most publishers don't get to make those deals, and most other agents don't get to have that access. That is the core mission of our business. We started with building products for AI customers. We've recently started figuring out what the incentives are for publishers to allow AI just to use them, which will include payments Mhmm. Which will include other forms of value, which is transactions, and which include distribution. Mhmm. Right? Which would be which are the things that people care about on the web. I've sort of having run Twitter before, I understand the concerns of someone publishing on the web and business models around ads are likely to evolve, and that's part of the reason we end up doing this company because we think we have an opinion or two to bring to life shares.

Speaker 2: Do large revenue multiples scare you?

Speaker 4: No. Good. No. As long as you know what you're doing. There we go.

Speaker 1: It's confidence. I love it.

Speaker 2: Love the confidence. Gotta be confident. Congratulations. But, yeah, I I I love how the the even even since the last your last appearance, you know, the vision, and opportunity, just seems bigger and bigger. Totally.

Speaker 1: Yeah. Makes a ton of sense.

Speaker 4: Thanks for having me.

Speaker 2: Yeah. It's great to have you back, at this rate. I'm sure, come back on the end of the year.

Speaker 1: Weeks and then make it around.

Speaker 4: I'm gonna ship a product in a couple of weeks and be right back.

Speaker 1: Fantastic.

Speaker 2: Head us up then.

Speaker 1: Congratulations. We'll talk to you soon, Prague. Have good one.

Speaker 4: Thanks for having me. Bye.

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