Profound raises $96M Series C at $1B valuation, launches autonomous marketing agents to manage brand presence across AI platforms

Summary

Profound raised $96M in Series C funding at a $1B valuation, led by Lightspeed Venture Partners with participation from Sequoia, Kleiner Perkins, Avantic, Saga, and South Park Commons. The company is launching Profound Agents, a product that expands its platform beyond monitoring how brands appear in AI systems like ChatGPT and Gemini to building autonomous agents that automate marketing workflows.

Founder James Cadwallader describes the expansion as completing a full-stack platform. Harvey has Harvey for lawyers, Cursor has engineers, and now marketers have Profound. The product addresses a gap Profound observed among customers who were taking the company's data and insights to third-party automation tools. By building orchestration directly into the platform, Profound lets marketers create customized agents without leaving the product.

Unlike search, which consolidated around Google, AI answer engines will remain fragmented with multiple competitors fighting for prominence. That fragmentation means brands need to manage their presence across platforms rather than optimize for a single algorithm. Profound now works with 10% of the Fortune 500. Cadwallader says large organizations move faster than commonly assumed on AI initiatives, particularly teams with SEO backgrounds who understand content distribution.

Cadwallader walked through a concrete case of misinformation correction. A neobank faced incorrect model claims about FDIC insurance, traced to a third-party blog, Reddit posts, and YouTube videos. The solution was not technical retraining but marketing: correcting the sources, commenting on Reddit, and publishing authoritative content. Profound Agents can now monitor for such misinformation automatically and generate outreach emails to source websites, though each agent requires customization to a brand's tone and priorities.

Cadwallader also announced Profound University, a certification and training program to develop what he calls the "marketing engineer" — a marketer with technical skills to customize and deploy agents across teams.

On terminology, Cadwallader rejected GEO (generative engine optimization) as confusing given the geographic meaning of the term and because these platforms are not actually called generative engines. Answer engine optimization is more accurate, though he expects the category will eventually transcend the label as how AI systems discuss brands becomes a fundamental marketing primitive.