Gumloop, a startup that builds tools for non-technical employees to create AI agents for task automation, has secured a $50 million Series B investment led by Benchmark. The company's platform is now used by teams at major firms like Shopify and Instacart to deploy reliable, multi-step AI agents, fostering widespread internal adoption.
The investment comes amid intense competition in the AI automation space from platforms like Zapier and Anthropic. Benchmark's lead investor believes Gumloop's advantage lies in its intuitive, low-learning-curve interface and its model-agnostic flexibility, which allows customers to choose the best AI model for specific tasks.
Main topics: Gumloop's business growth and funding, the competitive landscape for AI agent builders, and the key advantages (ease of use, flexibility) driving its adoption.
When Max Brodeur-Urbas co-founded Gumloop in mid-2023, his vision was to help non-technical employees automate repetitive tasks using AI. At that time, the concept of AI agents was still largely experimental and prone to errors.
As AI technology has matured, so has Gumloop’s offering.
The company claims that it now allows teams at organizations like Shopify, Ramp, Gusto, Samsara, Instacart, and Opendoor to deploy reliable AI agents that autonomously handle complex, multi-step tasks, all without ever needing an engineer.
Employees can share the agents they build with colleagues, creating a compounding effect that accelerates internal automation. “They get addicted, they start building more agents, and then all of a sudden, the whole company is AI native,” Brodeur-Urbas told TechCrunch.
As companies race to adopt AI, Benchmark general partner Everett Randell believes the key to success lies in empowering every worker with AI superpowers, and Gumloop’s intuitive agent-builder is an example of the kind of tool that will unlock that potential.
That’s why Randell, who joined Benchmark last October from Kleiner Perkins, chose to lead a $50 million Series B investment into Gumloop. The deal, which is Randell’s first at his new firm, included participation from Nexus VP, First Round Capital, Y Combinator, Box Group, The Cannon Project, and Shopify.
Though Gumloop wasn’t actively seeking new capital, the startup decided this was the year to “step on the gas.” For Brodeur-Urbas, partnering with Benchmark—the firm behind icons like eBay, Uber, and Dropbox—was a “no-brainer.”
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While Brodeur-Urbas previously planned to ‘build a 10-person, billion-dollar company,’ the surging demand from enterprise clients has compelled him to build a dedicated sales force and scale up his engineering team, he said.
Gumloop is by no means the only player vying to turn every knowledge worker into an AI agent-builder. The startup faces stiff competition from established automation platforms like Zapier and n8n, as well as specialized agent builders like Dust. Even foundational AI labs are entering the fray. For instance, Anthropic’s Claude Co-Work allows users to create autonomous agents without writing a single line of code.
But Randell believes Gumloop is superior to all its rivals. During his due diligence, he discovered that at least one of the company’s customers had adopted Gumloop somewhat organically.
When Randell asked a CTO how they chose Gumloop, the response was telling. The company had given employees full access to Gumloop alongside two competitors. Six months later, the results were clear: staff were using Gumloop daily or weekly, while the competing tools sat untouched, Randell told TechCrunch.
The reason Gumloop gained such momentum, according to Randell, is its minimal learning curve. “You can go in and start making agents and workflow automations immediately,” he said.
While many AI startups worry that foundational models will replicate the same functionality and render them obsolete, Randell is convinced that Gumloop’s model-agnostic approach is precisely what will keep attracting customers.
As models continue to evolve, one may perform better than another for a specific task. So, Gumloop provides the flexibility to choose the model best suited for the job at any given moment.
Another reason why model independence is attractive, according to Randell, is cost. “Plenty of enterprises have OpenAI, Gemini, and Anthropic credits. They want to use all of them,” he said
Randell’s excitement for the company ultimately comes down to the sheer size of the opportunity.
“Enterprise automation is a massive pot of gold,” he said. “I think it’s the biggest category in enterprise AI.”
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