While many startups are busy building “wrappers”, companies based around existing AI models, Gnani.ai, an Indian AI company, is not interested in building just another AI interface. The company has taken a different path and is building a proprietary AI model designed specifically for the large-scale Indian market.
At the India AI Impact Summit, I got a chance to speak with Ganesh, the co-founder of Gnani.ai, and I got some interesting insights about AI in the Indian landscape. Let’s take a look at what I learned from our conversation.
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In my conversation with Ganesh, I learned that Gnani.ai positions itself as a leader in the voice AI space. As per him, rather than simple chatbots, the company is more focused on creating digital workers for massive enterprises. He explained that their services are heavily in the finance sector, where they work with a majority of the private and public sector banks.
“We specialize in particular on voice AI and we help enterprises solve their core business problems.” Furthermore stating, “We work with almost every banking and financial services customer in the country including 3 of the top 5 private brands, 4 of the top 7 public sector banks, 2 of the top 3 gold loan companies.”
Given the high claims, I also wanted to understand from Ganesh what role Gnani has played. He explained that by using voice AI, they have managed to automate and humanise the payment reminder and interaction process; he suggests that they have changed how debt is managed in India.
“We have helped banking and financial customers collect more than 20,000 crores in the last 6 months.” Furthermore, “We have voice AI systems that remind customers, help them with their payment process and have an interaction. It’s all an interactive communication that helps them understand the best way to make their payments and help them with their payment process.”
Ganesh also explained his reason to avoid being like the rest, and he suggested that’s why they’re interested in building their own tech. While speaking about wrapper companies, he said, “They have no chance, especially on the voice side. Because firstly, you can’t get the right accuracies that you need to solve these problems.”
Deep diving into this point, he suggests that, “From a volume standpoint and from a scale standpoint, you won’t be able to scale because you need to have products with very low latency. And on the cost standpoint, if you use external APIs in this sector, it’s all expensive. So your cost will be more than what you get from a customer.”
Lastly, he also claimed that wrapper companies will not have a future and won’t be sustained for a long time. That’s because, as per him, “You can fool investors for some time, but not for very long.”
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