Evertune AI

Evertune is a New York-based AI visibility and Generative Engine Optimization (GEO) company founded in 2024 by Brian Stempeck, Ed Chater, and Poul Costinsky. The company helps brands understand how AI systems such as ChatGPT and other answer engines describe, recommend, and rank them across digital discovery experiences. Generative Engine Optimization (GEO) refers to the discipline of measuring and improving how brands appear inside AI-generated answers, recommendations, and conversational search experiences.

The founding team brings deep roots from The Trade Desk and AdBrain, combining large-scale advertising infrastructure experience with machine learning expertise. Evertune's platform focuses on AI visibility measurement, content activation, AI-driven discovery intelligence, and emerging advertising capabilities tied directly to conversational interfaces. The company recently announced a $15M Series A led by Felicis Ventures and has reported approximately $19M in total funding across multiple rounds. Investors include Eniac Ventures, NextView Ventures, Roger Ehrenberg, and a collection of strategic angels from OpenAI, Meta, Uber, Antenna, and other technology organizations.

The broader significance extends beyond one startup. Evertune sits at the center of a rapidly emerging shift in digital marketing where AI-generated answers are beginning to influence consumer discovery as much as traditional search results once did.

About Evertune

Every major platform shift creates a new scoreboard. Search created SEO. Social media created follower counts and engagement metrics. Programmatic advertising created entirely new categories of software dedicated to bidding, attribution, and optimization. Artificial intelligence is creating another scoreboard. The difference is that many companies do not yet know where the points are being kept. Evertune was founded to solve that problem.

The company positions itself as an AI visibility and Generative Engine Optimization platform designed to help brands understand how AI systems perceive them. As conversational interfaces increasingly become destinations rather than gateways, marketers face a challenge that feels familiar and unfamiliar at the same time. Consumers are still searching for information. They are simply receiving answers differently. Instead of ten blue links, they get a recommendation. Instead of a search result, they get a synthesized opinion. For brands, that changes everything.

Why Evertune Matters Right Now

Technology history has a habit of repeating itself with new costumes. A decade ago, executives debated whether social media deserved budget allocation. Years later, organizations fought over attribution models for mobile advertising. Today, boardrooms are having remarkably similar conversations about AI discovery. The question sounds simple: How does a company influence what AI says about its brand? The answer is considerably more complicated.

Large language models synthesize information from thousands of sources, citations, reviews, content assets, and authority signals. Traditional SEO strategies remain relevant, but they are no longer sufficient for understanding visibility within conversational systems. That gap has become Evertune's opportunity. As ChatGPT, Gemini, Claude, Perplexity, and other AI systems become part of everyday consumer behavior, businesses need measurement frameworks that extend beyond rankings and keyword positions. Evertune is attempting to build that framework.

Evertune is also part of a growing New York AI and marketing technology ecosystem that is increasingly producing infrastructure companies focused on enterprise AI adoption, data intelligence, and next-generation customer acquisition.

The Problem Evertune Is Solving

Marketing teams historically operated with relatively clear feedback loops. A campaign launched. Traffic increased. Conversions were measured. Results were reported. AI-generated discovery introduces ambiguity. A consumer may ask an AI assistant for the best CRM platform, running shoes, cybersecurity vendor, financial planning solution, healthcare provider, or enterprise software platform. The recommendation arrives instantly, but the underlying logic remains difficult to observe.

For brands, that creates a visibility problem. If an AI system recommends competitors more frequently, references outdated information, or overlooks a company entirely, traditional analytics tools often provide limited explanation. Evertune addresses this challenge through a combination of AI visibility measurement, GEO intelligence, content activation, and AI-focused advertising products. Company materials reference capabilities including Prompt Volumes, AI Usage, Topic Relevance, Brand Relevance, Content Studio, Shopping Intelligence, and the Visibility Boost Ad Agent for ChatGPT.

The company's core thesis is straightforward: brands cannot optimize what they cannot see.

Leadership and Team

One reason Evertune has attracted attention is the pedigree of its leadership team. Brian Stempeck, CEO and Co-Founder, spent 11 years at The Trade Desk and served as the company's first commercial executive. According to company materials, Brian Stempeck helped scale The Trade Desk from its earliest stages through IPO and into a business valued at approximately $50B. Ed Chater, CPO and Co-Founder, and Poul Costinsky, CSO and Co-Founder, first worked together at AdBrain before joining The Trade Desk following AdBrain's acquisition. Their backgrounds combine machine learning, identity infrastructure, and advertising technology expertise.

The broader executive team includes Matt Cochran (CTO), Rob Perdue (COO), Jaclyn Ranere (CMO), Mike Kalmakis (SVP Product), and Kelsey Platt (SVP Business Development). The common thread is notable. Many leaders have experience building platforms during periods of major market transition. That matters because GEO itself remains an emerging category rather than an established software segment.

Market Context

The GEO market exists because search behavior is changing. Not disappearing. Changing. Consumers increasingly rely on conversational systems to summarize information, compare options, and narrow decisions. The result is a new layer of influence sitting between brands and customers. Historically, marketers optimized websites. Today, they increasingly need to optimize how AI systems interpret those websites.

That distinction may sound subtle. It is not. Traditional search focused heavily on discoverability. AI discovery introduces interpretation. The model is no longer simply finding information. It is deciding how to explain that information. That creates new strategic questions around authority, citations, trust, content structure, and visibility. Evertune's emergence reflects broader market demand for answers to those questions.

Evertune operates within a rapidly emerging ecosystem that includes answer-engine optimization platforms, AI visibility analytics vendors, SEO software providers expanding into AI discovery, and enterprise marketing intelligence platforms adapting to conversational search. The category itself is still taking shape, which makes early infrastructure providers particularly interesting to watch. The company has also referenced recognition within discussions surrounding the emerging Answer Engine Visibility category, including Gartner-related market coverage highlighted through company communications.

Funding, Investors, and Market Confidence

Evertune announced a $15M Series A led by Felicis Ventures, with participation from Eniac Ventures, NextView Ventures, Roger Ehrenberg, and strategic angels connected to OpenAI, Meta, Uber, Antenna, and UVA. Reported total funding stands at approximately $19M.

The funding itself matters, but the investor profile may be even more interesting. Felicis Ventures has a long history of backing category-defining companies across AI, infrastructure, developer tools, and enterprise software. Their involvement signals growing investor conviction that AI visibility and answer-engine optimization could become durable parts of the modern marketing stack. Investors rarely fund categories they believe will remain niche.

Why Hiring Momentum Matters

When startups hire aggressively, the job openings often reveal more than the press releases. Evertune's hiring activity suggests demand is expanding beyond early experimentation. Organizations generally do not invest heavily in category-building talent unless customers are asking for solutions faster than existing teams can deliver them.

The company has sought talent spanning engineering, AI strategy, customer-facing functions, and commercial roles. Viewed through a market lens, that hiring activity reflects growing enterprise interest in AI visibility as an operational discipline rather than a theoretical concept. The signal is not simply that Evertune is hiring. The signal is that AI discovery is becoming budget-worthy.

What This Signals for Marketing Technology

Marketing technology periodically reinvents itself around changing consumer behavior. Search created SEO. Social media created social analytics. Programmatic created demand-side platforms. AI-generated discovery is creating visibility infrastructure.

Evertune is part of a broader movement attempting to define how businesses measure influence inside conversational systems. Whether GEO ultimately becomes its own standalone category or evolves into a larger AI marketing ecosystem remains an open question. What appears increasingly clear is that enterprise organizations want answers. The winners may not be the companies building the loudest AI products. They may be the companies helping brands understand how those AI products shape decisions.

The Bigger Industry Shift

Every technology cycle produces a moment when a new behavior becomes normal. The behavior arrives first. The software follows. The budgets arrive later. AI-driven discovery appears to be entering that phase.

Consumers are increasingly comfortable asking machines for recommendations. Brands are beginning to recognize that recommendation visibility requires measurement. Investors are funding companies positioned to provide that measurement. Evertune sits directly in that current. The company's future will depend on execution, category adoption, and the pace at which AI interfaces continue reshaping digital discovery. Regardless of outcome, the problem Evertune identified is unlikely to disappear. Once answers become products, visibility becomes infrastructure.