Runable, an Indian startup that builds AI agents for small businesses, has raised $21 million in Series A funding to expand its platform beyond software creation into customer acquisition and business growth. The round was co-led by Susqueaducture Venture Capital and Nexus Venture Partners, with participation from existing investors Together Fund and Array VC. The all-equity round values the Bengaluru-based company at $65 million post-investment, according to co-founder and CEO Umesh Kumar.
Founded in 2025, Runable targets small businesses in a market crowded with AI giants like Anthropic and OpenAI, as well as coding platforms such as Cursor, Lovable, and Replit. The 15-person team has built an AI agent that can find customers, run ad campaigns, create presentations, and promote businesses across search, social media, and AI chatbots. Kumar said the goal is to help business owners achieve real outcomes, such as managing Google Ads at a lower cost than hiring an agency, rather than simply generating code.
The company began as an AI infrastructure startup focused on browser-based data scraping, but pivoted after users increasingly asked its agent to create slide decks and websites. That shift helped Runable reach a $2 million annualized revenue run rate within three weeks of launching payments in March, Kumar said. The agent currently lets users build websites, apps, and presentations using natural language prompts, while handling deployment and analytics. Runable is now extending the agent to manage ad campaigns, social media, SEO, and a business's presence in AI chatbot results.
Runable reports about 1.7 million registered users, with the U.S., UK, and Japan among its largest markets. The startup is increasingly focused on those three countries and expects Japan to become a top market alongside the U.S. as soon as next month. Kumar declined to disclose current revenue or paying customer numbers, but said users consumed more than 1 trillion tokens over the last 90 days, with 60% to 70% of that usage coming from paying customers.
The heavy usage comes with a financial cost, as Kumar acknowledged that Runable currently has negative gross margins, partly because it subsidizes AI usage for customers. The startup is working with a mix of models, including developing its own, and expects falling inference costs to improve its economics. Kumar said the company sees a path to providing the same quality of inference at nearly 10 times lower cost.
Runable faces the challenge of differentiating itself as the AI model companies it relies on build their own agents. Kumar argued that Runable's advantage is handling the full scope of work needed to produce outcomes for small businesses, including infrastructure, analytics, and distribution, without requiring users to stitch together multiple services. In a test by TechCrunch, Runable built and deployed a website for a fictional coffee subscription business and prepared an ad campaign, but stopped short of running the ads because an advertising account was not connected. The startup said it can currently run ads without a customer's own account for ChatGPT placements, citing partnerships it declined to identify.
Kumar noted that Runable is not trying to beat coding agents at their own game, acknowledging that tools like OpenAI's Codex or Anthropic's Claude Code may suit developers working with local files. Instead, Runable targets nontechnical small business owners who want to avoid configuring the tools needed to turn an AI-generated product into a functioning business. General-purpose agents such as Manus and Genspark are viewed as Runable's closest competitors, Kumar said, but Runable aims to stand out by helping businesses find customers using AI, not just build with it.
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