One rapidly growing area within the generative AI landscape is customer support. This focus makes sense, considering the technology's ability to reduce contact center expenses while enhancing scalability. However, critics worry that generative AI in customer support may lower wages, cause job losses, and ultimately degrade the user experience. In contrast, supporters believe that generative AI will empower employees by allowing them to concentrate on higher-value tasks rather than replace them.
Jesse Zhang aligns himself with the latter view, though his perspective may be influenced by his own ventures. Along with Ashwin Sreenivas, Zhang co-founded Decagon, a generative AI platform designed to streamline various aspects of customer support.
Zhang is well aware of the fierce competition in the AI-driven customer support market, which includes tech powerhouses like Google and Amazon, as well as emerging startups such as Parloa, Retell AI, and Cognigy—recently funded with $100 million. Market estimates suggest this sector could soar to $2.89 billion by 2032, up from $308.4 million in 2022.
Zhang believes Decagon’s engineering expertise and marketing strategy offer a competitive edge. "Initially, we were advised against entering the customer support arena due to its saturation," Zhang shared. "Ultimately, we succeeded by prioritizing customer needs and maintaining a sharp focus on delivering real value. That’s the key differentiator between a genuine business and a fleeting AI showcase."
Both Zhang and Sreenivas boast robust technical backgrounds. Zhang's experience includes a stint as a software engineer at Google, an internship at hedge fund Citadel Securities, and the founding of Lowkey, a social gaming platform that was acquired by Niantic, the creator of Pokémon GO, in 2021. Meanwhile, Sreenivas worked as a deployment strategist at Palantir before co-founding Helia, a computer vision startup sold to unicorn Scale AI in 2020.
Decagon primarily targets enterprises and high-growth startups, developing advanced customer support chatbots. Powered by both first- and third-party AI models, these bots can absorb a company's knowledge base and analyze past customer interactions for better contextual understanding.
“While building the technology, we learned that developing ‘human-like bots’ requires addressing the complex reasoning and analytical abilities that human agents possess,” Zhang explained. “Feedback from customers shows that everyone desires increased operational efficiency, but it must not compromise the customer experience—nobody appreciates subpar chatbots.”
So, what sets Decagon’s bots apart from traditional chatbots? According to Zhang, they adapt based on historical conversations and user feedback. More significantly, they can seamlessly integrate with other applications, enabling actions such as processing refunds, categorizing messages, or drafting support articles on behalf of customers or agents.
On the administrative side, businesses benefit from comprehensive analytics and management tools for Decagon's bots and their interactions. “Human agents can leverage conversation analytics to detect trends and identify areas for improvement,” Zhang noted. “Our AI-driven analytics dashboard autonomously reviews and categorizes customer conversations to highlight themes, flag anomalies, and suggest knowledge base additions for more effective customer support.”
Despite generative AI’s reputation for sporadic inaccuracies—sometimes leading to ethically questionable outputs—Zhang assures companies that they need not be concerned about issues like incorrect advice or data leakage. "It's vital for us to provide customers with relevant safeguards and oversight for their AI agents," he stated. “We tailor our models to individual customers while ensuring that no data can inadvertently be shared. For example, a model used to generate answers for customer A has zero access to customer B's data."
Recently, Decagon has attracted several notable clients, including Eventbrite, Bilt, and Substack, positioning the company for break-even status. Prominent investors like Box CEO Aaron Levie, Airtable CEO Howie Liu, and Lattice CEO Jack Altman have also joined the venture.
To date, Decagon has secured $35 million through seed and Series A funding rounds, with participation from backers such as Andreessen Horowitz, Accel (which led the Series A), A*, and entrepreneur Elad Gil. Zhang emphasizes that this funding is directed toward enhancing product development and growing Decagon's workforce based in San Francisco.
"A major challenge is that customers often associate AI agents with outdated chatbots that fell short of expectations," Zhang remarked. "The customer support sector is flooded with these legacy systems, which have damaged consumer trust. To succeed, new solutions must break through the clutter created by incumbents.”
Ranking
