New York AI Marketing Company Profound Completes $180 Million Series D, Valued at $1.8 Billion
Profound Completes $180 Million Series D Valued at $1.8 Billion
New York AI marketing company Profound has completed a $180 million Series D funding round, valuing the company at $1.8 billion, with Sequoia and Kleiner Perkins co-leading the investment. Lightspeed, Khosla, Saga, South Park Commons, and new investor Evantic participated in the round. Founded in 2024, the company has raised over $335 million in total funding.
This round comes less than seven months after the $960 million Series C round, which had a valuation of about $1 billion. The company's products have expanded from monitoring brand mentions in ChatGPT, Perplexity, Gemini, and Google AI summaries to research, writing, deployment, and agency orchestration. The company has launched AI Marketer (Aim), Context Manager, and Ads Studio, and plans to establish application labs in New York and San Francisco for model retraining in marketing scenarios.
Profound has over 1,000 corporate brand clients, including Comcast, Estée Lauder, Walmart, Zoom, ServiceNow, Ramp, Cursor, MongoDB, Figma, Campari, and the Royal Bank of Canada. The company claims to cover over one-third of the Fortune 100, with about 16% of the Fortune 500; external reports have mentioned 18%. In the past six months, the company claims its revenue has grown approximately threefold, although it has not disclosed absolute revenue figures.
Co-founder James Cadwallader stated that clients have used agencies for research, writing, and reporting, and the new platform aims to enable marketing teams to undertake campaigns they previously lacked the capacity for. External commentary highlights three aspects of the company's competitive advantage: analyzing over 100 million AI responses monthly across about 18 countries; establishing "marketing engineers" as trusted contacts for target audiences; and training domain toolkits using AEO data, existing tools, and business context.
Market-wise, this represents a new budget entry point as search shifts from links to answers: brands are purchasing visibility and messaging in model responses, while selling is limited to old SEO contracts that only optimize Google blue links. Beneficiaries include monitoring companies that have stockpiled response data; those under pressure include modules in Salesforce and Adobe Marketing Cloud that have yet to separately allocate "answer engine" budgets, as well as a plethora of GEO/AEO tools. The rapid doubling of valuation compared to public revenue indicates that pricing is still based on category bets rather than profit margins.
Additionally, Sequoia and Kleiner have led three out of the four funding rounds for the company. Monitoring and recommendations remain the primary focus, while implementation and public relations execution are largely left to client teams.
Source: Public Information
ABAB AI Insight
Profound is writing the next page of SEO as AEO, and using the same batch of corporate clients to expand analytical tools into agency workspaces. The $1.8 billion valuation is not just for a dashboard but for the tax rights of the migration where models start selecting brands for users. The 100 million monthly responses represent a differentiated data layer; without this layer, agencies would only produce attractive but uncalibrated copy. Cadwallader's use of "marketing engineers" as a label shifts buyers from SEO specialists to market leaders willing to pay for the new structure.
In seven months, capital has increased the valuation from $1 billion to $1.8 billion, with Sequoia and Kleiner leading three rounds, which is a typical category-capping investment: first establishing monitoring standards as industry defaults, then packaging the execution layer. New funds entering labs for backward training in marketing indicate that general models are not vertical enough and must use brand data to weld agencies into client contexts. The entry of Walmart and Estée Lauder serves as a procurement endorsement for the remaining Fortune 100.
In comparison to early SEO tools, Semrush/Ahrefs' keyword databases, and the expansion of Adobe Experience Cloud's suite, the industry phase is characterized by answer engines capturing part of the search entry points, while marketing budgets have yet to complete the renaming of categories. Whoever first owns cross-model, cross-country mention data will define "how well it appears." Salesforce still controls the process, but the process has yet to include the metric of "how ChatGPT introduces it."
The structure reflects the transfer of pricing power brought about by technological substitution. The discovery path has shifted from ten blue links to a segment of generated text, with optimization targets moving from webpage rankings to data and citations. The mechanism is: as user questioning methods change, brands must purchase their statistical rights in responses; once statistical rights are established as corporate standards by one company, agencies can sell execution based on the same scoring system. If scores are proprietary, new tax collectors will emerge in the category.
ABAB News · Cognitive Laws
When search becomes answers, the optimization target shifts from links to data.
100 million monthly responses are more like a competitive moat than just another writing agency.
Before categories have their own subjects, valuations are paid for the right to rename.