Profound Raises $180M as AEO Becomes Enterprise GTM Priority
On September 15, 2026, Profound raised $180 million in a Series D round co-led by Sequoia Capital and Kleiner Perkins at a $1.8 billion valuation. The company had closed a $96 million Series C less than seven months earlier, in February 2026. The pace of successive rounds reflects something more than investor enthusiasm: it reflects the speed at which enterprise GTM teams are reckoning with a structural shift in how buyers find and evaluate products.
That shift is Answer Engine Optimization, and Profound is now the company Sequoia, Kleiner Perkins, Lightspeed, and Khosla Ventures are betting will define the category.
The Problem: Buyers Are Asking AI Instead of Googling
Traditional SEO is built on a clear signal: someone types keywords into Google, gets a ranked list, clicks a link. Enterprises have spent two decades building content, backlinks, and technical infrastructure to rank well in that list.
The list is no longer the destination.
More than 100 million people a day now open ChatGPT, Gemini, or Perplexity to research products instead of starting with a Google search. These systems do not return a ranked list of links. They generate a written answer, synthesizing hundreds of sources into a single response. A brand that ranks on page one of Google can be described incorrectly, incompletely, or not at all in that generated answer.
“As buyers turn to Answer Engines like ChatGPT, Gemini, and Perplexity to research products and compare brands, marketers have infinitely more surface areas to cover,” Profound said in its funding announcement. “Answer Engines will use hundreds of thousands of sources to form their opinion of just one brand.”
That complexity is why AEO has moved from a niche experiment to a board-level topic at enterprise marketing organizations. Gartner formalized the trend by naming Profound a Representative Vendor in its inaugural Market Guide for Answer Engine Visibility Tools, published earlier in 2026.
What Profound Builds
Profound’s platform has three interconnected layers, each addressing a distinct stage of the AEO workflow.
AI Search Insights. Built on more than 2 billion real user prompts collected across AI platforms, Profound’s analytics surface exactly which prompts buyers use to research products, how AI models describe each brand in response, and where gaps or inaccuracies exist. Teams can benchmark their AI visibility against competitors and track it over time as AI models update.
AI Marketer. Launched as part of the Series D announcement, AI Marketer is Profound’s core agentic product: a marketing expert agent that scans brand data, analyzes AI answer patterns, identifies visibility opportunities, and deploys sub-agents to execute work. It finds earned media openings, proactively refreshes stale content that AI models rely on, runs competitive analysis, and coordinates campaign execution.
AI Marketer operates through Context Manager, a persistent system that synthesizes a company’s knowledge base files, meeting transcripts, and communications into a living brand profile. When positioning changes, Context Manager updates automatically, so the AI Marketer adapts without requiring marketers to re-brief it from scratch.
Ads Studio. Profound’s newest product extends AEO into paid media. Ads Studio lets teams build, launch, and optimize AI search campaigns across OpenAI, Google, and Meta’s ad platforms from a single interface. The AI Marketer handles creative generation at scale, batch edits across campaigns, root cause analysis on underperforming ads, and bidding optimization. Profound provides its own pixel to track results independently of platform-reported metrics.
Enterprise Adoption at Scale
Profound now serves more than 1,000 enterprise brands, including over one-third of the Fortune 100. Named customers include Comcast, Walmart, U.S. Bank, Zoom, ServiceNow, Figma, Ramp, MongoDB, and DocuSign.
The results reported by customers underscore why adoption has accelerated. Ramp, the corporate finance platform, reported a 7x increase in AI brand visibility for its accounts payable product after deploying Profound. That metric matters because enterprise software buyers increasingly research finance tools by asking ChatGPT or Perplexity rather than submitting contact forms to trigger a sales sequence. Being described accurately in that AI answer is now a precondition for even entering the consideration set.
A joint study Profound conducted with Listen Labs found 90% of CMOs now use large language models daily, with 85% reporting increased LLM usage over the prior six to twelve months. Those figures align with the company’s claim that it is the fastest-growing AI marketing platform in the enterprise segment.
“The world’s largest brands are moving fast to put AI to work across their marketing teams, and Profound has established itself as the applied AI lab they rely on,” said Anas Biad, Partner at Sequoia Capital.
What the $180M Round Funds
The Series D capital goes toward three priorities: growing Profound’s applied AI labs in New York City and San Francisco, expanding global enterprise sales, and post-training frontier models specifically for marketing tasks.
The research agenda is notable. Profound is assembling a team of research scientists, economists, and competition mathematics medalists to develop a benchmark for measuring how well AI models handle complex marketing assignments. That benchmark will evaluate whether models can understand a business, weigh competing market signals, and produce high-quality marketing outputs across functions. Research findings will feed back into improvements to the AI Marketer.
This approach mirrors what domain-specific AI companies like Harvey (legal AI) and Salesforce (CRM reasoning) are doing: post-training general frontier models on domain-specific data to produce systems that outperform general-purpose models on specialized tasks. For marketing, the unique signal is Profound’s dataset of 2 billion real buyer prompts, which no competitor can easily replicate.
| Metric | Profound (Sep 2026) |
|---|---|
| Valuation | $1.8 billion |
| Series D raise | $180 million |
| Total funding | $335+ million |
| Enterprise customers | 1,000+ brands |
| Fortune 100 coverage | More than one-third |
| Buyer prompts in dataset | 2 billion+ |
| CMOs using LLMs daily | 90% (Listen Labs study) |
| Lead investors | Sequoia Capital, Kleiner Perkins |
Why This Matters for Enterprise GTM Teams
The Profound raise is a signal, not just a funding event. When Sequoia and Kleiner Perkins co-lead a $180 million round at a pace that doubles valuation in seven months, they are pricing in a category that is moving from experimental to essential.
For enterprise GTM teams, the implication is direct: AI answer engines are now the primary discovery interface for a large and growing segment of buyers. That means marketing spend on content, earned media, and paid search needs to account for how AI systems interpret and describe brand assets, not just how those assets rank in a list of links.
Teams that treat AEO as a complement to existing SEO programs will find it increasingly necessary to treat it as a first-class channel. The buyers asking ChatGPT “what is the best accounts payable software for mid-market finance teams” are making purchase decisions based on the answer they receive, not the links listed below it.
The operational implication is scale. Answer engines draw on hundreds of thousands of sources to form a view of each brand. Keeping those sources accurate, consistent, and updated at the pace AI models refresh their training is not a task a small content team can handle manually. The AI Marketer’s case for existence is that it can run that operation at a scale humans cannot.
Enera’s approach to autonomous GTM systems maps directly to this shift. As the surface area of enterprise brand presence expands to include every source an AI model might reference, the teams with automated, AI-native marketing operations will build a compounding visibility advantage over those still relying on manual content cycles.
What Enterprise Leaders Should Do Now
The practical steps for GTM and marketing leaders are straightforward:
Audit your current AI visibility. Use a platform like Profound or run manual prompt tests across ChatGPT, Gemini, and Perplexity. Ask the questions your buyers ask. Verify that your products are described accurately, favorably, and completely.
Identify your highest-value discovery queries. Buyers ask AI specific questions, often more specific than Google keyword research reveals. Map those to your products and assess where gaps exist.
Update the sources AI models use. AI systems ground their answers in content they can find: company websites, documentation, press coverage, third-party reviews, and structured data. Ensuring those sources are current and accurate is the foundation of AEO.
Integrate AEO into paid media planning. AI search advertising is now available across OpenAI, Google, and Meta platforms. Brands that run early experiments will accumulate data advantage as bidding and targeting mechanics mature.
The enterprise marketing stack is being rebuilt around AI as the discovery interface. Profound’s $180 million raise, closing in under seven months since the previous round, measures how fast that rebuild is happening. For GTM leaders, the question is no longer whether to address AEO. It is how quickly they can build the capability before their competitors do.
To explore how an AI-native GTM system can address AEO at enterprise scale, book a call with the Enera team.