Emergent raises $130M Series C at $1.5B valuation as its no-code AI platform crosses 200K customers and $100M ARR

or automating business workflows, Codeex helps you move projects forward from start to finish. And our next guest is with us from Emergent with a huge, huge series C. Let's bring in Makun. How are you doing? Welcome to the show.

Hi John. Hi Jordy. I'm doing great. How are you?

Congratulations. Give us a quick introduction, reintroduction to the company and tell us the news.

Yeah, I'm so excited to be here. So, Emergent is an AI platform that allows nontechnical business owners build and deploy production grade applications. Um, and we are increasingly becoming an operating system for small and medium businesses

to become more AI native. Um, we just recently announced $130 million series C round at 1.5 billion valuation.

Congratulations. Fantastic. Um um there's uh right now I mean it feels like obviously there's a ton of knowledge retrieval that's happening and uh with AI in enterprises and businesses. Uh there's also agentic workflows that once they are established they are running in they're doing inference but they're doing that 24/7 even while the workers are asleep. And then there's the different work which is uh helping you build new deterministic systems whether that's vibe coding agentic engineering context engineering all of that. Um what has been the bigger driver more recently? Has it been coming in understanding a manual workflow for a company building a AI powered system that can do that on repeat forever uh and then moving on to the next problem? or has it just been enabling business users and engineers to constantly work with AI and build new systems iteratively? Yeah. So for us like most of our users are nontechnical u almost 80% of our users are nontechnical and these are business operators you know who are running small and medium businesses across the globe and um and we we are a platform where they can come in and in national language describe what they want to build uh both agents and applications um and we have you know people who are building custom CRM ERPs inventory management tool a lot of the business critical tools that they're building right now is getting deployed you know on emergent and the power is that most of these people understand their business really well. They understand the domain. They understand the problems that they're trying to solve but haven't had access to technology teams um or or dev shops, quality dev shops to sort of really build these software

and because we able to bring the cost down dramatically for them like they're able to experiment and and you know really accelerate their business today.

What's

where are you where are you finding customers? You're at over 100 million of ARR 200,000 customers. Where are they all coming from?

Yeah, so we are actually fairly well distributed right now. One third of our revenue comes from North America, one/3 from Europe, one/3 from Asia

and um you know most of these users are essentially you know nontechnical business owners right now and there is a huge variety of you know breath of users coming you know from from people who are running hospitals to people who are running factories to you know people who are running travel agencies all of them coming in building their own sort of you know production grade software

where's the where's the sweet spot right now for AI adoption in your customer base because when I hear uh you know custom CRM system I'm I think small business that is sort of starting for starting fresh like uh TBPN we have you know 10 employees and we have built a whole bunch of custom internal systems but if we were a thousand person company or a 10,000 person company it's a much different conversation even as powerful as the tools are to rip out a salesforce and that's certainly not showing up with the the lack of the SAS apocalypse that didn't really materialize in revenue declines for the SAS companies. Um, and so am I am I correct in thinking that like the smaller, more agile, smaller businesses are potentially more ready to adopt uh custom tooling that's built from AI agents like your own?

Yeah, totally. Totally. I mean uh the users that are coming to our platform are traditionally businesses that have been running on top of emails, WhatsApp, spreadsheets.

Yeah.

And now they're trying to digitize themselves. Many of them are active new entrepreneurs who, you know, understand their domain really well, have a new idea that they want to build. And essentially a lot of these, you know, small businesses um I mean I believe that they're going to just skip the SAS cycle and move to the AI cycle directly.

And that's what we are seeing right now. A lot of these, you know, businesses have a lot of excitement and and they understand their domain really well and they're able to relate with with the problems that they're solving. and um and they come in on the platform, you know, try to build something simple like a landing page first and then they sort of go on to building more complex use cases on the platform.

Yeah. Uh from your work in Asia, do you have any insight? We we we have always heard this stat that uh like 90% of Americans don't like AI. In China, it's reversed. 90% love AI. Uh do you have any insight into what uh the mood, the hot topics of conversation are in India or other other parts of Asia? uh outside of just the US China dynamic. Yeah, I think there's a lot of excitement in India across you know around the board for AI and I think you know adoption is increasing at a very very fast pace right now and um you know I think we recently had this AI summit also in India you know last year

that brought a lot of excitement and generally I think you know like everybody is super excited about you know using these tools uh you know and we also have like a large developer base so CEX cloud code all of those things are really popular and uh you know people are finding new ways to use AI to sort of accelerate their businesses today.

Sure. Sure. Um what what about employment? There there was uh I remember listening to sort of an AI doomer who was uh talking about the risk that AI would create mass unemployment uh internationally because some of the outsourced BPOS or call center work would be displaced immediately. I've been tracking those employment numbers and I haven't seen uh a massive fall off but do you have any insight into what's happening in the international labor markets? I mean right now I think um at least for short period of time like I feel and that's what we're seeing also is that employment is going to go up because you know like

um you know especially like in in in domains like software and bunch of those things

where you know as software is is becoming cheaper and cheaper to build I think you know like the demand and the need for software is actually accelerating so we are seeing you know jobs actually increase um but but you know as we get closer and AI has become more powerful you know like trends may change.

Yeah. uh how h what are you hearing from your customers on demand for uh closed source frontier expensive tokens uh versus uh laggered models versus open- source models like how quickly do you abstract all of that cost consideration or do you have opinionated users that say I want to use a 5.6 soul or a fable because I heard something about that abstractly but I want to use it within your harness and within your product.

Yeah. So typically we we actually abstract those things out and and you know we have a model router which figures out depending on your request what is the best model to use. Uh even during the execution we would switch to open source or you know some of the cheaper models if if you see the task is relatively cheap to do and uh in fact like you know as you know all the labs are pushing out on this test time compute. Yeah. uh the actual cost of building is actually going up even though token price is doing the same. Uh and and often time we see that um you know like there is there is a sweet spot of affordability and and and price and value right that we we're trying to keep. Yeah.

Uh and increasingly we're seeing that you know like now that frontier models are getting really really good and open source is also getting really good. Uh this mixture approach is what what is working really well for us.

Yeah. Yeah. Yeah. It's it's fascinating uh just being in this era where uh for the first time in my life certainly like technology has a marginal cost and we're we're all talking like uh like railroad baronss now or or manufacturing uh you know it's uh it's just so different from the world of zero marginal cost.

Yeah. The the other thing is just just how many companies doing functionally the same thing can all be growing so quickly, right? Like certainly you have a lot of competitors from from uh from Labs to uh Lovable, Replit all these companies and yet you're all they're all doing really well.

They're fantastic businesses.

Uh and it's and it's cool to see.

Yeah, I think there's a huge amount of latent demand in the market right now like as people, you know, really discover the power to build things and and eventually we think that product that is able to deliver, you know, final outcome to the users is is eventually going to win and and I think that's where we you're doing really good. Yeah, that's amazing. Well, congratulations.

Great update. Congrats to the whole for coming back to the show.

Thank you so much for having me.

Have a good one. Let me tell you about the New York Stock Exchange. Want to change the world? Raise capital at the New York Stock Exchange. We also have some amazing breaking news. The all-time record has been hit for a dinosaur sold at auction. Sbees just sold Gus the T-Rex for $50.1 million. Finally. of dinosaurs.

Someone's doing the math. 183 bones going into this T-Rex. That's $273,000 per bone.

Per bone. Interesting. But the sum is greater than its parts in this case.

This is truly an incredible example.

I do wonder.

Imagine having this in the Ultra Dome.

I feel like I feel like many Yes, I I agree. I feel like many uh dinosaur skeletons are often found uh with some bones missing and so they have to recreate some of those. I wonder uh this is probably an extremely complete example but I wonder how many uh how complete it actually is uh relative to uh what's possible like the theoretical max.

In other news last year just 20% of adults accounted for more than 80% of all books read

power and everything. And this account says, "Wow, 20% accounted for 80%." An unprecedented and unique dynamic.

Uh I mean, there are people that just churn through books. And uh I mean, if you count the number of books that you read to a small child, it's like four or five books a day, right? You're putting up like five books a day, right?

You're more like 10, 15, 10, five.

Yeah. Something like that.

Yeah.

Pretty good. Pretty good. You add that up, you're probably Do they count parents reading children's books in this stat? Because that changes everything because a parent will honestly read thousands of books. Cat in the Hat might get read a 100, 200 times in a single year. That's going to thist every night for months, sometimes. Yes, I know. We've all been there. Anyway, moving on. Breaking news from thinking machines just launched a new model and it's open weight. It's called Inkling.

Interesting.

Inkling reasons efficiently across text, image, and audio modalities. We are making the full weights available.

Fun on hugging face probably. Uh well, we'll have to go check it out. See how it benchmarks, see how it reviews, see if it can do our benchmarks, our