The Struggles of Building an AI Startup in India
Ashwin Raguraman’s Bharat Innovation Fund began to invest in AI in 2018, starting with traditional technologies like computer vision, voice recognition, and recommendation systems. It was only in 2021 that GenAI emerged as a game-changer driven by large language models. This shift helped freshly minted Indian startups like Sarvam AI and Krutrim develop localised solutions. And now, it is layering into middleware (security and observability) and applications leveraging traditional and generative AI. So, as AI startups stagger into 2025, let’s find out just how difficult it is to build an AI startup in India. If you have a great startup idea, a business plan, and a suitable location, you just need to tap into the funds and get started. Unfortunately, it’s not as simple as it sounds. Stanford’s 2024 AI Index Report ranked the nations that have witnessed the most growth in AI startup activity over the last decade. According to the report, the US and China ranked at the top, while India held the seventh position. India’s AI Funding Game AIM earlier reported that it is now a prime time to build an AI startup in India due to funding opportunities and acquisition potential. According to AIM Research, 43 Indian AI startups received $864 million in funding as of August 2024. Among these, Ema, an enterprise AI startup, raised $36 million in Series A funding. Established players such as Uniphore and Gupshup are leading the pack with late-stage funding rounds, as per Tracxn data. Uniphore raised $400 million in Series E funding (January 2022) and $140 million in Series D (November 2020). Similarly, Gupshup secured $240 million in Series F funding (July 2021) and multiple $100 million rounds, showcasing sustained investor confidence in AI-driven solutions. Emerging players like Sarvam AI and Krutrim are also making waves in the industry. Sarvam AI raised $41 million in Series A funding (December 2023), signalling strong early-stage support. Krutrim, a generative AI-focused startup, has attracted $50 million in Series B funding (January 2024) and $24 million in Series A (July 2023), demonstrating consistent growth and innovation in cutting-edge AI applications. Institutional investors such as Tiger Global Management, Lightspeed Venture Partners, and Alpha Wave Global are leading the funding of Indian AI startups. These global and angel investors are enthusiastically backing AI innovations, highlighting the country’s growing prominence in the global AI landscape. In terms of valuations, companies receiving higher funding amounts, such as Uniphore and Gupshup, have valuations ranging from $1 billion to $2.5 billion, contributing to India’s expanding unicorn ecosystem. This reflects the increasing confidence in the potential of Indian AI companies to create large-scale global impact. The diversity of AI applications is another hallmark of the Indian startup ecosystem. While established companies focus on conversational AI solutions, emerging players are diving into generative AI and specialised areas like text-based chatbots. For example, Senseforth is carving a niche in enterprise chatbots, while Krutrim and Sarvam AI are pioneering generative AI platforms. Funding for AI startups in India totalled $8.2 million in the April-June 2024 quarter. In contrast, AI startups in the US received $27 billion in the same period, representing nearly half of all startup funding in the country. The upside? Building products in India is far less costly than in the West. Abhijeet Kumar, CEO of Tablesprint, underscores India’s unique cost advantage. “Building a solution like Salesforce would cost millions in the US, but in India, it’s a fraction. India is no longer just a service provider; we’re creating products that compete globally. For AI startups, now is the time to build in India, with talent, resources, and cost advantages all in place.” Are Bengaluru’s AI Startups Tempted by the Bay Area? For some founders, India provides what’s needed to build impactful, cost-effective technology. Amritanshu Jain, co-founder and CEO of SimpliSmart, who returned from Silicon Valley, is even more convinced. “In India, we have a deep pool of tech talent. Many think Indian engineers leave for the US due to a lack of opportunities here, but that’s changing.” Yet, Vedant Maheshwari, CEO of Vidyo.ai, believes India’s core challenge in AI lies elsewhere. “Foundational AI requires significant capital and patience, which is harder to secure in India. While funding here is substantial, it’s mostly application-focused rather than foundational,” he explained. “In the US, there’s more support for deep-level work, but in India, targeting specific AI applications allows us to leverage existing models without huge initial investments.” Vishnu Ramesh of Subtl.ai, who has ties to both the Bay Area and India, sees it as a matter of investor confidence. “The Bay Area draws investors because of its track record. Once India has its ‘Google moment’, confidence here will rise.” Also, most IITians prefer to move to the US for better opportunities. According to the US-based National Bureau of Economic Research, one-third of those graduating from the country’s engineering schools, particularly the IITs, live abroad. Brendan Rogers, co-founder of 2am VC, shared on LinkedIn that most of these IITians are unicorn founders. The Hybrid Model India excels in application development; however, GenAI demands fresh talent and innovation. While government initiatives like the National AI Mission foster upskilling, startups continue to struggle. As a result, many look abroad, especially to the US, which offers faster adoption cycles, larger contract sizes, and better ROI on AI products. As there is an evident pattern of startups moving to the US, the country continues to be a key market for Indian AI startups. It also provides higher annual contract values (ACVs), making it attractive for startups seeking rapid growth. Many founders adopt a hybrid model – operations and talent in India with customer bases in the US – leveraging India’s cost advantage and the SaaS model to scale globally. Raguraman said Indian AI startups are mostly focused on enterprises rather than consumers. “The enterprise market here is an excellent testbed due to discerning customers who demand rigorous product evaluations. However, the slower adoption rates and smaller ACVs compared to the US remain a challenge. This disparity often compels startups to focus on international markets for growth while maintaining a foothold in India,” he said. What’s Next? What venture capitalists look for while evaluating AI startups is, how much effort they have invested in their technology, what proprietary data they control, and the unique value they’re adding over existing models. This effort should be substantial, so they are confident it’s not just a surface-level improvement but something with real depth. Indeed, India offers a more capital-efficient startup environment, whether for AI, or otherwise. However, the question is whether this will remain the case as these businesses scale globally. Once startups expand and start competing internationally, they will need to invest in talent from around the world, which could increase their expenses. In terms of capital, India requires less funding for startups compared to the US, but there is also significantly less capital available here. While the Indian VC and startup ecosystem has grown substantially, it’s still relatively young and about 60 to 70 years behind the US ecosystem.
According to AIM Research, Indian AI startups received $864 million in funding as of August 2024.
AIM earlier reported that it is now a prime time to build an AI startup in India due to funding opportunities and acquisition potential.
["Startups in Bangalore"]
["Startups in Bangalore", "GenAI", "AWS", "AI", "chatbots", "recommendation systems", "computer vision", "RAG", "Aim", "generative AI", "edge AI"]
["AI", "computer vision", "generative AI", "GenAI", "Aim", "edge AI", "RAG", "chatbots", "recommendation systems", "AWS"]
Vidyashree is enthusiastic about investigative journalism. Now trying to explore how AI solves for all.