Sales cycles for India’s business-to-business (B2B) artificial intelligence (AI) startups have started shrinking, as a growing number of companies move to rapidly embed the technology into their ecosystems.
While companies were earlier cautious and sought proof of concept, or a small pilot, to test whether AI tools worked before rolling them out across their operations, they have now moved past that hesitation and are deploying these tools much faster at scale.
“This year, we've been taking less than three months to hit production at scale with our enterprise customers,” said Ganesh Gopalan, co-founder and chief executive at voice AI startup Gnani. “Companies didn't want to do proof of concept projects anymore, they now want to do field trials in production.”
Indian B2B startups have traditionally preferred to sell to overseas enterprise customers, primarily due to the drawn-out sales cycles and lengthy proof of concepts (PoCs) back home. But, with AI becoming standard in Indian boardroom conversations, chief information officers (CIOs) and chief technology officers (CTOs) are being pushed to implement the technology across their company's ecosystems. At the same time, they need to also show that their investments are increasing efficiencies and improving performance.
“There's no doubt that top to bottom, everyone is being pressured to show what they can do with AI, how they can increase efficiencies and effectiveness. The pressure is high,” said Alok Goyal, partner at early-stage venture capital firm Stellaris Venture Partners.
Companies like Gupshup and Gnani have seen their sales cycles shorten as a result of the urgency that companies are showing when it comes to deploying AI.
“Companies end up doing PoCs because they want to make sure the technology is working in their context and their situation,” said Beerud Sheth, chief executive of Gupshup, a business messaging platform that enables companies to communicate with customers. “But if you're able to iterate quickly on their requirements, which is what has happened with AI, you can finish a sales cycle that would [otherwise] take months, in weeks.”
More than half of Gupshup's business comes from the Indian market. But in order for the company to be able to close sales faster, it required reimagining its own teams, as well as the technology they use.
As a result, the startup changed how its sales teams function, as well as the technology they use. In April, the company launched Superagent, an orchestration AI agent for marketing and sales.
Deccan AI, which provides high-quality human-curated data, model training and evaluation services to frontier AI companies in the US, is now looking to expand into India. The startup, which raised $25 million in a Series A round in April led by A91 Partners, is launching an enterprise business in the country, focused on global capability centres.
As part of the Hyderabad-based company's push into the enterprise business, the company is exploring mergers and acquisition (M&A) opportunities to not only bring existing customers into the fold, but also showcase the improvements their technology brings to enterprises. “We naturally expect sales cycles to get shorter once we've demonstrated what we can do with a few big logos,” said company founder Rukesh Reddy. “By the end of the year, we're expecting a serious chunk of our revenue to come from enterprise customers.”
Deccan AI is prepping an enterprise-grade product called Helix, which works with a human-in-the-loop workflow to ensure that the AI tool doesn't make errors.
Much like Gnani, Deccan AI has no intention to be just doing PoCs for enterprise customers, instead opting to work with companies that are serious about deploying AI models into their workflows.
Boosting business
Shorter sales cycles, which have so far been unheard of in India's B2B AI and software ecosystem, have prompted companies to project more growth than in previous years.
For Gnani, Gopalan said that the company has closed 100 new enterprise contracts in the past six months and that they're growing 2-3X more than the previous year.
Meanwhile, Gupshup has seen a whole new market segment open up, as AI has made closing sales calls easier, while also showcasing performance improvements to existing customers.
Earlier, small and medium businesses were not part of the company’s strategy, as the cost of serving them outweighed their ability to pay. But AI has changed that because the product is at a level where Gupshup doesn't have to put in too much service effort for customer deployment, adding to the overall number of paying customers.
“Conservatively, we're expecting a 2X-5X increase in new logos we have over a given time period,” Sheth said. He added that Gupshup was able to renew one of its existing enterprise customer contracts in just one meeting, as they were able to create four iterations instantly, as opposed to going back and forth for months.
While companies say that they're expecting a boost in business, venture capital investors are more cautious, citing decision making within enterprise as the key barrier.
“With the world of AI, I think there's massive confusion for enterprises,” said Goyal of Stellaris Venture. “If a company is buying new software for use across its ecosystem, it takes at least a year before it starts showing value.” He added that for decision makers, there's also a very real fear of the technology they bought in year one, becoming obsolete by year two. “Fundamentally, sales cycles aren't changing too much in our view, because it's still choreographing a large number of people to agree to one thing.”