From YC to AWS: How 8.5 Million People Build Software on Emergent Without Writing Code

In less than a year, Emergent has become one of the fastest-growing startups in the world. In a journey that has captivated the industry, the vibe coding platform reached $100 million USD in annualized revenue just eight months after launch, surpassing 8.5 million users across 190 countries. And 80 percent of their users have never written a single line of code.

This rise comes at a time when AI-powered coding tools are proliferating. But while many platforms focus on developers, Emergent has built its platform around a different audience entirely: people with great ideas, but little coding expertise.

For Emergent, extraordinary growth has created extraordinary technical demand. With Amazon Web Services (AWS) infrastructure, the company has built a reliable foundation to support its scaling ambitions, allowing access to AI inference capacity and ensuring its users can continue building applications without interruption.

Founded by brothers Mukund and Madhav Jha and accelerated through the Y Combinator (YC) summer 2024 batch, Emergent’s journey spans two continents, multiple startups, and years of experience building AI.

Two brothers, one idea

Madhav and Mukund came to the US separately to complete their PhDs, before both pursuing careers in frontier technology. Mukund worked at Google before co-founding India’s pioneering delivery platform Dunzo, while Madhav was part of the team building Amazon SageMaker, witnessing first-hand how AI has evolved through waves of innovation.

"We'd been wanting to build something together for a long time,” explains Madhav. “We spent years on separate paths before finally deciding this was the right time to jump into AI together."

Their initial idea was focused on end-to-end UI testing. Having seen for themselves the growing use cases and impact of AI, as well as how laborious and slow UI testing was for developers, Mukund and Madhav started work on automating the entire UI testing workflow.

Pivoting their purpose

In 2024, Emergent participated in YC’s summer batch, giving them space to refine their business model and greater exposure to the wider startup community. But as soon as the program commenced, the team realised that their potential opportunity was much larger than they’d imagined.

“On the first day of YC, we told them that we wanted to pivot,” says Madhav. “We entered with an idea around UI testing, but very quickly we realized that there was an even bigger opportunity to automate the entire software development lifecycle.”

YC supported Emergent’s idea, helping the startup reason through their new direction before they started building. Madhav adds, “The community aspect of YC is a force multiplier that keeps compounding over the years, as we’re now able to reach out to fellow entrepreneurs, partners, and YC alumni. It helps to immerse yourself into that environment where everybody is working to be at the frontier of innovation.”

The period after YC was spent almost entirely researching and testing. “We spent the first six months of the startup in research mode trying to build the world's best coding agent,” says Madhav. “When we came number one on SWE-bench Verified benchmark, we realised we'd built, at that time, the best coding agent on the market.”

Building AI for everyone

Now the technical groundwork was in place, the founders faced a new question: who were they building it for? Initially, the team explored selling into enterprises, but lengthy sales cycles pushed them towards a different audience. Rather than competing for developers’ attention, Emergent realized there was an even larger group being overlooked entirely.

Madhav explains, “One of the ways we productized it was to build the coding agent for non-developers.” With much of the coding market focused on engineers, Emergent pivoted to entrepreneurs, founders, and small business owners. In other words, users with big ideas, but few technical skills to bring them to life.

And while its competitors often focus on generating prototypes or proof-of-concepts, Emergent wanted users to build products they could actually launch. “Most platforms were offering a simple layer on top of your idea,” says Madhav. “But it might not stand up when you shipped it to customers. With Emergent, users don’t build projects, they build production-ready software.”

From day one of using Emergent, users can build not only the front-end experience, but also the back-end infrastructure, databases, and integrations required to launch a complete application. “The customers who became our power users aren’t hobbyists, they’re entrepreneurs and small businesses who are serious about building and shipping their apps.”

But beneath the simplicity of the platform’s interface is an exceptionally powerful engine. The months spent building Emergent’s underlying coding agents before launch gave the platform an advantage that elevated it above its competitors.

“We were probably the only startup at that time which had a real developer-grade coding agent,” says Madhav. “The product is very user-friendly, but at the same time, the thing that fuels it is also very powerful.”

Scaling one of AI’s fastest-growing startups

Emergent's momentum was apparent almost immediately after launch. “It became pretty clear within the first 30 days,” says Madhav. “We were off to such a good start that we were able to close our Series A very quickly.”

But building an AI platform at this scale requires not just powerful models, but also reliable access to infrastructure. At the time, securing AI inference capacity was a challenge across the industry, with fast-growing companies struggling to access the resources they needed to meet demand. For Emergent, making sure their customers could continue building seamlessly, with no interruptions, was a top priority. This made AWS a natural choice.

“AWS went above and beyond for us to secure the right set of rate limits capacity for us. And that was extremely pivotal for our growth,” says Madhav. “Once we have the backing of a partner like AWS, then we can go pretty aggressive on our marketing and growth because we know that when customers come, they're not going to face downtime and they're not going to have a bad experience.”

To meet demand, Emergent moved its production AI workloads onto Claude Platform on AWS (CP on AWS), Anthropic's enterprise-grade inference platform that runs exclusively on AWS infrastructure. In doing so, it became the first company in the world to run its entire production workload on the platform. The move allowed them to handle every user request at scale while maintaining a reliable customer experience.

Expanding beyond inference

The partnership with AWS is also extending beyond AI inference alone. As AI agents become more capable, the infrastructure challenge is shifting. “We’re in a world where not everything has to go through one model,” Madhav explains. “There’s a lot of delegation: testing apps, running scripts, doing research… all of which requires compute that can spin up and down instantly.”

As Emergent continues to grow, AWS is becoming an increasingly important partner across those workloads too, helping the company with the elasticity and flexibility needed to build its infrastructure and support millions of users around the world.

AWS has also played a key role in Emergent’s go-to-market and ecosystem efforts. In late 2025, AWS, YC, Anthropic, and Emergent launched a joint startup hackathon, bringing together nearly 3,000 applicants from around the world. “The camaraderie was really good,” says Madhav. “It felt like everybody was on the same mission and everyone was united towards making this successful.”

“We’ve been able to fall back on AWS on a more personal level, not just a technical one,” he adds. “When challenges come up, we focus on how we solve them together.”

Emergent’s future focus

Emergent’s ambitions now extend far beyond software development. The company is evolving from an AI app-building platform into what it sees as a new operating system for businesses, one where you can not only build the app itself, but also run the business through a powerful suite of specialized agents that act as AI employees and communication through messaging channels like WhatsApp, Telegram and iMessage.

“We want to be a platform which brings AI to everyone in the world, so nobody feels left out,” says Madhav. “These capabilities are powerful, but they only matter if they are accessible in a form people actually want to use.” Already, Emergent is extending beyond web and mobile app creation into broader business use cases, including customer support, lead generation, and operational workflows. AWS continues to provide the underlying infrastructure that allows the company to scale its ambitions.

At the core of Emergent’s mission is the belief that AI should feel familiar, practical, and deeply embedded into how people already build and run businesses. “We think similarly to Amazon in its focus on customer obsession,” says Madhav. “Everything we build starts from what users actually need to succeed.”