AI coding startup Emergent has become India’s latest unicorn after raising $130 million in a Series C funding round led by Creaegis, with participation from MNI Ventures-Claypond Capital, Sentinel Global, Khosla Ventures, SoftBank, Lightspeed and Y Combinator.
The round values the San Francisco-headquartered company at $1.5 billion, underscoring the rapid pace at which artificial intelligence startups are scaling globally.
The company is the sixth Indian startup to attain unicorn status this year and the second AI startup after Sarvam to achieve the milestone in recent months.
Founded by former Dunzo co-founder Mukund Jha, Emergent develops an AI-powered vibe coding platform that enables users to build, test and deploy software applications using natural language prompts, reducing the need for traditional programming skills.
The fresh capital will be used to expand product and engineering teams while strengthening the company’s go-to-market presence across Asia, the US and Europe.
“We believe we’re one of the best app builders for serious production-grade applications globally. This funding will help us widen our technology lead,” Jha told FE.
Slashing Costs
Jha said the platform aims to dramatically lower software development costs for small businesses. According to him, an application that may traditionally cost between $100,000 and $500,000 to build can be developed on Emergent’s platform for less than $5,000 while maintaining enterprise-grade functionality and security.
More than 12 million applications have been built on the platform since its launch. Around 20-30% of users are business owners building or digitising their businesses, with small and medium enterprises contributing nearly 70% of the company’s revenue.
While North America and Europe remain its largest markets, Jha said India is emerging as a fast-growing opportunity as more businesses look to digitise.
“India is still significantly under-digitised. As AI tools become simpler and more affordable, we see a large opportunity for businesses that have never built software before,” he said.
Jha also said improving AI model efficiency and greater adoption of open-source models are helping reduce costs, improving margins for AI application companies that rely on foundation models.