Gushwork, an agentic AI startup raised a $9 million seed funding spherical led by Susquehanna Asia VC with participation from Lightspeed, B Capital, Seaborne Capital, Beenext, Sparrow Capital, and a pair of.2 Capital.

Based by Nayrhit Bhattacharya and Adithya Venkatesh, Gushwork has constructed a swarm of advanced AI advertising brokers to assist small and medium companies get found and cited on AI search engines like google and yahoo like ChatGPT, Claude, Perplexity & Gemini, serving to them generate extra leads and get new clients.

The startup stated it would use the raised capital to speed up product improvement, enhance the accuracy of brokers, increase engineering groups, and scale go-to-market operations.

“Consumers have already began shifting their behaviour, asking AI for vendor opinions as an alternative of salespeople or buddies for referrals. By 2028, AI’s advice would be the main method patrons select their distributors,” stated Nayrhit Bhattacharya, CEO and Co-founder, Gushwork AI.

“We have constructed autonomous AI brokers that guarantee enterprise’ web sites get advisable by AI when their patrons ask these questions. This $9 million increase and help from an skilled group of traders validates our imaginative and prescient and can assist us speed up our product construct and go- to-market velocity.”

“For each human go to, we’re seeing 2x-3x AI agent visits on our buyer web sites. This creates a basic shift, the place a web site wants to draw not simply human guests, however AI guests as nicely which can analyze and cite the content material when answering potential clients’ questions,” says Adithya Venkatesh, CPO and Co-founder, Gushwork AI.

“Now we have constructed a data-backed and deeply technical content material creation, distribution, and administration engine that plugs instantly into any web site and constantly attracts each AI crawlers and human patrons. Our brokers are at all times adapting and evolving as these AI fashions, which routinely maintain updating each few days, ” he explains. “The technical moat lies in understanding how completely different AI engines consider authority, how they cluster subjects, and the way they resolve what to quote.”