Indian startup Runable has closed a $21 million Series A round to expand its AI agent’s scope from creating websites and apps toward helping small businesses find customers and grow. The round was co-led by Susquehanna Venture Capital and Nexus Venture Partners, with existing investors Together Fund and Array VC also participating. The all-equity primary round valued Runable at $65 million post-money, the company said.
What Runable does and the product shift
Founded in 2025 and based in Bengaluru, Runable employs about 15 people. The company began as an AI infrastructure startup focused on browser technology and large-scale data scraping, founded by Umesh Kumar and Saksham Sarda. Over time, users increasingly asked the browser-based agent to create slide decks, websites and similar assets, prompting a pivot to a general-purpose AI agent.
Today Runable’s agent can build websites, apps, presentations and other content from natural-language prompts while handling parts of the underlying infrastructure such as deployment and analytics. The startup is now extending the product into what it calls the “grow” side: running ad campaigns, managing social media, handling SEO and optimising a business’s presence in AI chatbot results.
Umesh Kumar, co-founder and CEO, said the longer-term aim is for small business owners to tell Runable to acquire a set number of customers rather than separately set up a website, analytics, ad accounts and marketing campaigns.
Users, markets and revenue run rate
Kumar said Runable has about 1.7 million registered users, with the United States, United Kingdom and Japan among its largest markets; there are also users in Brazil. The company expects Japan to move alongside the U.S. as a top market in the coming month.
After launching payments in March, Runable said it reached an annualized revenue run rate of $2 million within three weeks. The company declined to disclose current revenue or the number of paying customers.
Runable also reported that users consumed more than 1 trillion tokens over the past 90 days, and roughly 60–70% of that usage came from paying customers.
Costs, margins and model strategy
Kumar acknowledged Runable currently operates with negative gross margins, in part because the company subsidises AI usage for customers. Runable works with a mix of models and is developing its own; it expects falling inference costs to improve economics over time. Kumar said they see a path to delivering similar inference quality at roughly one-tenth the cost.
Practical limits and advertising setup
One operational limitation is that running ads typically requires connecting a customer’s ad account. In a brief test, Runable’s agent built and deployed a website for a fictional coffee-subscription business, prepared an ad campaign to attract the first 100 visitors on a $25 budget, but did not run the campaign because it required an advertising account to be connected.
Runable said it can run ads on ChatGPT without customers connecting their own ad accounts via undisclosed partner relationships the company described as a “soft wedge.” The startup declined to identify those partners.
Competition and positioning
Runable competes in a crowded landscape that includes AI model companies building agents of their own — such as Anthropic and OpenAI — and coding- or creation-focused platforms like Cursor, Lovable and Replit. Kumar named general-purpose agents such as Manus and Genspark as close competitors targeting similar users and markets.
Kumar argued Runable’s differentiator is its focus on delivering business outcomes: not only building a product but managing the infrastructure, analytics and distribution necessary to produce measurable results for nontechnical small-business owners who don’t want to stitch together multiple services.
Conclusion
With $21 million in new funding and a stated $65 million post-money valuation, Runable aims to move beyond enabling AI-based creation toward directly helping small businesses acquire customers. The startup faces near-term challenges around negative gross margins and the need to distinguish itself as large AI providers build their own agent capabilities, but it is betting that integrated execution — from deployment and analytics to ad campaigns and chatbot presence — will be its competitive edge.
