Profound raises $180M to boost brands’ visibility in AI services
SiliconANGLE Maria Deutscher ● Covered by 3 sources
Profound raised $180M at a $1.8B valuation. It tracks what people ask AI tools so brands can show up more often.
Based on reporting by SiliconANGLE, Maria Deutscher — read the original for the full story.
Summary, retelling and take written by AI under human oversight; images are AI-generated illustrations. How we work · Report an error
Profound just turned a marketing problem into a very expensive one. The startup raised $180 million in a Series D led by Sequoia Capital and Kleiner Perkins, and the round values the company at $1.8 billion. Lightspeed Venture Partners, Khosla Ventures, Saga Ventures, Evantic and South Park Commons also joined in.
The company, officially Cooper Square Technologies Inc., sells a cloud platform built for the age of ChatGPT and its cousins. Instead of tracking clicks or search rankings, Profound looks at the prompts a brand’s target buyers use when they research products. Then it tries to help that brand show up more often inside chatbot answers.
A retailer selling electronics, for example, could use the system to see which ChatGPT queries people use when looking for smartwatches. Profound can surface the most popular prompts from the past week and pick out patterns in them, such as a focus on health tracking features. The idea is simple enough: if a company shapes its site content around the words buyers actually use with AI tools, chatbots are more likely to cite that content back.
Profound also wants to be more than a dashboard. It can check whether AI responses describe a company’s products accurately, measure consumer sentiment around offerings, and speed up competitor research by finding prompts that bring up rivals. In June, the company launched a tool for comparing a brand’s chatbot ads with competitors’ campaigns. Earlier this year it also rolled out Aim, a feature that plans AI visibility initiatives on its own, and later a tool that can generate chatbot ads automatically.
The new money will go into post-training AI models for marketing use cases and into a benchmark for measuring how well those models automate the work. Profound says the research should feed back into the product itself. That’s the real bet here: not just answering what buyers ask, but building software that starts doing the marketing chores for them.
My take — AI-written commentary, not fact-checked reporting
This is a neat business, and also a sign of where AI advertising is heading: from chasing clicks to chasing mentions inside model outputs. The funny part is that brands now need software to understand how software understands them. That feels less like marketing magic than a new tax on being visible online.
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