Why Indians Prefer Homegrown AI Startups to Big-Tech Companies
Sridhar Vembu, former CEO of Zoho Corp, recently highlighted the need to stop glorifying English in India’s R&D ecosystem. “There is a lot of R&D talent in India if we get rid of the English barrier and the social stigma of not knowing English well,” he posted on X. “I am right now working with extremely capable engineers on some advanced tech, and we converse in Tamil because that is what they are most comfortable with,” he added. While Vembu’s emphasis on local languages was one aspect of the discussion, the localisation of AI solutions is gaining momentum. Indian companies are increasingly preferring homegrown AI startups over big-tech firms. The Preferred Choice In a past interaction with AIM, MN Anucheth, the JCP of Bengaluru Traffic, spoke about the traffic department working with several homegrown AI startups to leverage AI solutions. “Since Bengaluru is the tech capital of India and a lot of AI-based startups are based in the city, we have been lucky enough to be able to work with many such companies,” he said. “AI has been made accessible to us, for which we would otherwise rely on some foreign import or off-the-shelf product, which generally do not work in real-time conditions.” The Bengaluru Traffic Police has collaborated with many Indian startups to enhance AI-driven traffic management. For instance, Monday Technologies supports AI avatars for awareness videos and drone-based monitoring to detect road blockages and accidents. Other key partners include IBI (the developer of ASTraM), Skita, and Matrix Technologies, with Videonetics as the OEM. Anucheth explained that continuous feedback helps refine models, such as improving seatbelt detection accuracy. Though big-tech firms such as Google and Cisco offer traffic management solutions, authorities prefer to maintain flexibility and control over their infrastructure. “Nothing against big tech companies, but I think our experience has been that we can’t work with them to give tailor-made solutions to us,” said Anucheth. Nuanced Approach From an investor’s perspective, VCs look to invest in Indian AI startups that offer nuanced solutions that big-tech companies cannot deliver. Citing Google’s PaLM models as an example, Capria Ventures’ explained to AIM how startups have an edge in understanding vertical-specific needs. In the health sector, especially hospitals, where the radiology department requires in-depth analysis, a local player has a better edge. “The big-tech models are going to be there to prove the science of the underlying technology they have, but they are not good at solving the vertical needs of what the radiology department at hospitals need, top to bottom,” said Will Poole, co-founder and managing partner of Capria Ventures, in an interview with AIM earlier. Poole cites 5C Network, which has spent seven years developing a specialised, end-to-end solution tailored for radiology departments. While AI models play a role, they are just one component of a much larger system. Big tech may develop powerful models, but access to high-quality, diverse medical imagery is essential for training effective AI. “What Kalyan, the founder of 5C, built was a network of hospitals from which he takes images. A radiologist can read those images… He’s done 11 million of them, adding, I don’t know, half a million per month,” Poole said. “Without that kind of data… you’re not going to be able to build an AI that’s as good as somebody who has it,” he added. Poole explains that for investors, the key lies in backing founders with proprietary data access, enabling them to scale rapidly and outpace competition. Indic Models Navana AI, a Bengaluru-based voice AI startup that develops indigenous AI-powered speech recognition and NLP solutions, told AIM that big tech companies posed a lot of problems when it was in the research phase of trying out interfaces with NLP. “We started using Google, Microsoft, AWS, all of the existing services that were out there, but none of them worked for Indian languages at that time. Even today, most don’t work for non-major languages or low-resource languages,” said Raoul Nanavati, co-founder and CEO of Navana ai. While big-tech companies have been collecting and building language data, it has mostly been English and Western languages such as French, German, and Spanish, as these native language users have been on the internet for decades. This has been a challenge for these companies when they build for India. “So there’s a cold start problem in India for language AI,” said Nanavati. Recognising this, the team decided in 2018-19 to develop indigenous speech recognition AI and NLP solutions for all Indian languages, overcoming the data scarcity that had hindered progress in this space. With the nuanced approaches each startup offers, enterprises are actively seeking to collaborate with Indian AI startups, a trend that shows promising potential.
VCs look to invest in Indian AI startups that offer nuanced solutions that big-tech companies cannot deliver.
VCs look to invest in Indian AI startups that offer nuanced solutions that big-tech companies cannot deliver.
["AI Startups", "Capria Ventures", "India", "JCP Anucheth", "Navana ai", "Will Poole"]
["Go", "API", "ELT", "AWS", "AI", "R", "RAG", "NLP", "Capria Ventures", "Aim", "Navana ai", "JCP Anucheth", "Will Poole", "India", "AI Startups", "startup"]
["AI", "NLP", "Aim", "RAG", "AWS", "R", "Go", "API", "ELT", "startup"]
As a rare blend of engineering, MBA, and journalism degree, Vandana Nair brings a unique combination of technical know-how, business acumen, and storytelling skills to the table. Her insatiable curiosity for all things startups, businesses, and AI technologies ensures that there's always a fresh and insightful perspective to her reporting. She now hosts her tech segment 'Point Break' on AIM Tv.