Bengaluru-based investment firm Creaegis led the round and was joined by India family office firm Claypond and Californian fund Sentinel Global. Existing investors Khosla Ventures, SoftBank Vision Fund 2, Lightspeed, and Y Combinator also participated.<\/p>\n
“We built Emergent for the non-technical entrepreneur and the small business owner, with 70% of our users having no prior coding experience,” said Mukund Jha, co-founder and chief executive of Emergent. About 12 million apps were built on Emergent in the last year by “small business owners and solo entrepreneurs,”\u00a0Emergent said.<\/p>\n
Exactly a month ago, India’s full-stack sovereign AI company Sarvam raised funds of $234 billion<\/a> from a clutch of investors, gaining a post-money valuation of $1.5 billion.<\/p>\n These developments are “consistent with broader momentum we’re tracking,” Deepika Giri,\u00a0head of research for AI, analytics and data at IDC Asia Pacific, told CNBC, adding that “nearly half of Indian enterprises are already testing agentic AI solutions.”<\/p>\n This is an “unusually fast experimentation and workforce automation at scale for a market this size,” she said.<\/p>\n Positive signals<\/p>\n Market research firm IDC expects 45% of Indian organizations to use specialized cloud services by 2026, to gain computing access, which will ease a key bottleneck for training and inference. \u00a0<\/p>\n It said India also has the broadest AI accelerator stack in APAC \u2014 spanning NVIDIA<\/a>, AMD<\/a>, and hyperscaler silicon \u2014 giving it a flexibility that most markets lack. An accelerator stack is any piece of hardware<\/a> that can be used to train AI workloads, while hyperscaler silicon refers to customized chips. <\/p>\n These factors, coupled with a vast engineering and AI talent pool, could help India shed its reputation as an AI laggard, experts said, but cautioned that these are still early days in<\/strong> that journey.<\/p>\n Sarvam’s funding reflects confidence that India can build “valuable intellectual property in indigenous and multilingual AI,” Mohammad Hassan, head of APAC dividend forecasting at S&P Global Market Intelligence, told CNBC. <\/p>\n Emergent’s fundraise highlights the strength of Indian technology talent, which could prove to be “India’s trump card in the long run AI race,” he added, calling the developments “positive signals” but not proof of a major shift.<\/p>\n India trails in the global AI race as it does not yet produce cutting-edge chips domestically, nor does it yet have a frontier-scale foundation model on a par with leading U.S. or Chinese models. Its data center capacity also\u00a0lags considerably behind<\/a>\u00a0the AI leaders.<\/p>\n But the South Asian country, which hosted a major global AI conference<\/a> this year, has been confident of making a mark in the AI space by building applications on top of foreign foundational models. <\/p>\n During the global AI summit in February, Indian Prime Minister Modi said that his vision was for India to be “among the top three AI superpowers globally<\/a>,” not just in terms of being a consumer but also a creator.<\/p>\n India being a major IT services exporter has the software talent to build AI applications for the globe, but securing unfettered access to foundational models<\/a> remains a key risk to its ambitions as countries are increasingly attaching strategic importance to this technology.<\/p>\n It will take “at least three to four years” for India’s AI ecosystem to grow to a point where it creates a “flywheel effect,” Neil Shah, vice president of research at Counterpoint Research, told CNBC’s “Inside India<\/a>” on Thursday. <\/p>\n![\"India](\"https:\/\/www.europesays.com\/ie\/wp-content\/uploads\/2026\/07\/108335802-17841881731784188170-47193773636-1080pnbcnews.jpg\")
<\/p>\n