Imagine you are a B2B AI start-up founder in India aiming to solve a tech problem in Indian IT. You spent years identifying a problem and defining your value proposition, conducting in-depth market research, and are now ready to execute your idea.
You begin assembling a core team, including technical co-founders, domain experts, a business/operations lead and others. Next, you develop a Minimum Viable Product (MVP), test it in real-world scenarios, pilot it with initial customers and iterate based on feedback.
You also register your start-up and ensure legal compliance, secure seed funding and plan your financial runway, build scalable infrastructure, refine your tech stack and finally implement a go-to-market strategy and execute sales.
Now that you are finally ready to sell your Software as a Service (SaaS) to Indian businesses, you are met with hour-long calls to explain your software details, multiple free Proofs of Concept (PoCs) with several iterations and extensive documentation requirements.
This keeps happening repeatedly, consuming a major chunk of your time and energy that should be invested in improving your software. You realise there is a lot of resistance in the system, making it nearly impossible to sell in India. Eventually, you decide to “skip India” and start selling to foreign clients.
This “skip India” sentiment was recently expressed by Vaibhav Domkundwar, CEO of Better Capital, and was supported by several AI founders.
In an X post, Domkundwar wrote, “AI founders are finally skipping selling to Indian customers after doing PoCs after PoCs and then being requested for even more free PoCs.”
He stated that these AI founders are 10x better than the internal team of the unicorn who are exploiting them for freebies. “There is a limit to this and the founders are saying screw it and skipping selling to Indian customers,” he added.
Domkundwar’s post ignited a public discourse on a topic that was earlier limited to the AI founders and VC circles. The topic is that it is hard to sell AI SaaS to Indian businesses.
The larger narrative around this issue blames the exploitative nature of Indian businesses which makes it difficult for Indian AI start-ups to serve in the country. However, is this narrative entirely accurate, or is the story more nuanced?
The Narrative: Problem with Indian Customers
Paras Chopra, founder of AI start-up Lossfunk, commented on Domkundwar’s post, stating that he has banned his team from talking to Indian customers. He described the Indian market as “a tiny tech market, but a comfort zone,” adding that “many times, founders end up optimising for the Indian market and realise they can’t scale further.”
Chopra’s comment signals that there is a major issue that AI start-ups face while attempting to serve Indian customers. Hence, they choose not to serve them.
A major chunk of Indian AI start-ups prefer serving foreign clients due to the relative ease of operating outside India, higher resistance from Indian customers and better returns on investment (ROI) abroad.
It is more convenient for a start-up to serve clients outside India as most foreign companies like those in the US follow a standard process that understands the importance of a start-up’s time and efforts.
Sharing his experience of serving US/European clients in contrast with Indian customers, Raj K Gopalakrishnan, CEO & Co-founder of KOGO AI said, “North American and European buyers typically allocate budgets for pilots upfront, view paid PoCs as standard and avoid endless negotiation over free work. Abroad, gatekeepers respect a start-up’s time and engineering investment from day one.”
Another reason it is challenging to serve Indian customers is the complex adoption process they follow, which becomes exhausting for start-ups and wastes their time and resources.
Srinivas Padmanabhuni, co-founder of AIensured remarked that Indian businesses are aversive of new-age concepts as compared to businesses in the West, hence their adoption process is more rigorous. “While in the West businesses are ready to experiment with new-age concepts due to the budget available and cost arbitrage, Indian businesses are more frugal and need a validated business case and clear cost-benefit figures before they invest. That makes sales cycles longer and difficult,” he said.
Adding to this, KOGO AI’s Gopalakrishnan said, “Indian market can feel tougher to serve than Western markets because the percentage of customers requesting free PoCs is significantly higher. I think it stems from our inherent cultural bent of “SASTA, SUNDAR, TIKAU”—a desire for maximum value at minimal cost.”
Foreign markets also offer a higher ROI compared to Indian markets, making it attractive for AI start-ups to focus on international clients.
Regarding the financial advantages of earning in dollars, Aswini Asokan, founder and CEO of Vue.ai, stated, “…the [Indian] market did not pay and like we say in our founder circles, earning a dollar is what a VC would call 'good revenue'. It was better quality revenue, easier acquired, easier serviced than the Indian rupee and as a result, earning a $ would get you way better valuation than earning a rupee.”
Conversely, Rajesh Bharatiya, CEO & founder of Peoplefy, attributed the challenge to the cost-sensitive nature of Indian customers. “Indian customers are traditionally highly cost sensitive. There is a definite cost of developing and running a SaaS application. However, some large Indian organisations throw their weight around their brand name and ask for free PoCs,” he said.
Counter Perspective: Missing Nuances
The above arguments substantiate how and why it is difficult to sell to Indian businesses. But does that mean AI start-ups can never sell their SaaS in India?
Several social and systemic factors shape the way Indian businesses adopt services. However, applying Western standards of SaaS adoption to Indian customers is a misguided approach.
In the public discourse of the issue, a critical detail missing is that the start-up founder must understand the market he is trying to sell in, including the social and behavioural nuances of the market.
Vue.ai’s Asokan explains this well. She said, “The most critical thing to understand about building a B2B AI business [is that] every time you choose a market to grow a business in, you need to learn the behavioural, social nuances of that market. If you understand that as a founder, invest along those vectors, align your expectations accordingly and lastly, incentivise your teams along those lines, you will crack that market. Very very simple. This is not rocket science. It's the difference between companies that understand people & markets and those that don't.”
When KOGO AI’s Gopalakrishnan stated that Indian businesses optimise for “SASTA, SUNDAR, TIKAU” service, he also noted that “plenty of Indian enterprises are not habitual freebie seekers and understand the effort–output–compensation calculus.”
“Once Indian enterprises are convinced of the idea they tend to stick longer with proven products, and the rate of switching to other vendors is much less compared to the West,” AIensured’s Padmanabhuni said on the same.
Contradicting Domkundwar’s claim that AI founders are skipping to sell in India, Asokan revealed that “Vue has grown its Indian presence exponentially in the last 18 months” with the growth of the AI market. She also stated that they tried selling in India 10 years ago and failed, signalling a growing tech reception in the Indian market.
Explaining the difference between the Indian and US markets, Asokan said, “Here — they expect people to show up, not just products. Like Kunal of Cred always says, this is a largely trust deficit market. So the only way to make the world go around here is through network, word of mouth, people showing up in front of execs and teams to be there as a partner. In the US, they don't want to see you. They want to see self-serve products that do all of it without having to reach out and talk to another person.”
So, should AI start-ups sell in India or not?
“Would I urge B2B companies to never sell in India? No… I would urge them to begin their journey in the US and then expand in India. India is not a laggard in AI adoption but it's not the leading indicator either. So launch in the US and grow in India is what I'd suggest,” Asokan stated.
