Sierra, an artificial intelligence (AI) startup focused on customer experience, has reportedly raised $950 million in new funding.
The new funding values the company, which makes AI customer service agents, at $15.8 billion, CNBC reported on Monday (May 6).
Sierra was founded three years ago by OpenAI chairman and former Salesforce co-CEO Brett Taylor and former Google executive Clay Baber. Taylor told CNBC that the company employs a “series of models” and its own fine-tuned proprietary layers.
The company announced annual recurring revenue (ARR) of more than $150 million in eight quarters. Taylor said this growth schedule is unprecedented for traditional software and highlights “intense market demand.”
“There’s a really large addressable market and pressing opportunity,” Taylor said. “We’re kind of digitizing the last remaining analog channel, the phone line. This improves the experience. You don’t have to be put on hold. These agents are naturally multilingual.”
Taylor estimates that $400 billion is spent annually on customer service, with most of that going to AI agents.
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Sierra raised $350 million last year, giving it a $10 billion valuation. CNBC reports that its customers include Prudential, Cigna, Blue Cross Blue Shield, Rocket Mortgage and more, as well as one-third of the world’s largest banks.
In other agent AI news, PYMNTS recently wrote about how the technology is moving “from a frontier technology to a stake at the operational table,” as evidenced by recent earnings releases from players like Visa and marketplace announcements from companies like Square and Ramp.
“Agentic AI represents a shift from tools that inform decisions to systems that execute them. For CFOs, this changes the calculus,” the report says. “The question is no longer whether artificial intelligence can improve financial operations, but whether it can do so within a framework of control and accountability.”
This is where the “Agent AI Harness” comes into play. Although this term may seem technical, its meaning is deeply operational. The harness is not the model itself, but the system that determines how the model functions in the real world.
“It defines what AI agents can access, what they are allowed to do, how they will be monitored, and when they must defer to human judgment,” PYMNTS added. “For chief financial officers, understanding this layer has become as important as understanding internal controls and capital allocation.”
