Evertune Pitch Deck: All 17 Slides + Teardown

Evertune's 17-slide deck successfully articulates a shift in consumer behavior: the migration from Google search to AI-powered chat interfaces like ChatGPT and Perplexity. By positioning themselves at the intersection of SEO ($68B), Brand Monitoring ($45B), and Search Advertising ($306B), the company makes a compelling case for a new category of marketing analytics. The deck uses specific luxury SUV case studies to demonstrate how LLMs currently rank brands and, crucially, identifies why certain content is excluded from AI training sets due to crawler blocks. While the deck is light on team c…

Key takeaways

• The deck identifies a massive shift in search scale, noting OpenAI has 200m weekly unique users compared to LinkedIn's 160m (Slide 3).
• Evertune defines its value proposition through three pillars: understanding LLM output, identifying training content gaps, and providing action steps for brand education (Slide 7).
• The platform provides a proprietary 'AI Brand Index' that benchmarks brands across different models like GPT-4.0, Gemini, and Llama 3 (Slide 7).
• A luxury SUV case study demonstrates radar charts measuring 'Top of Mind,' 'Perception,' and 'Media' across different LLMs (Slide 9).
• The deck highlights a technical friction point: brands and publishers blocking AI crawlers, which prevents models from learning about their products (Slide 11).
• Competitor benchmarking data shows specific 'Content Block Rates,' such as Porsche having a 39% block rate for OpenAI crawlers (Slide 13).
• Evertune targets three massive legacy markets: SEO ($68B), Brand Monitoring ($45B), and Search Advertising ($306B) (Slide 15).
• The deck omits a dedicated team slide, financial ask, and roadmap, focusing instead on the market shift and product utility.

Frequently asked questions

What is the core problem Evertune is solving?

Evertune addresses the 'black box' nature of Large Language Models (LLMs) for marketers. As consumers move from Google to AI chatbots, brands lose visibility into how they are being recommended. Evertune provides the analytics to see what LLMs say about a brand and identifies the specific content or technical blocks preventing AI models from accurately learning about a brand's products.

How does Evertune measure brand performance in AI?

The company uses an 'AI Brand Index' and radar charts to score brands on metrics like 'Top of Mind,' 'Perception,' 'Price,' and 'Product.' These scores are segmented by specific models, such as GPT-4, Gemini-Pro, and Llama-3.1, allowing brands to see where they are winning or losing in the AI-driven recommendation engine.

What is the significance of the 'Content Block Rates' mentioned in the deck?

This is a critical technical insight. Many websites use robots.txt or other methods to block AI crawlers. Evertune shows that if a brand like Porsche blocks 39% of OpenAI's crawlers, the resulting AI answers about Porsche will be incomplete or outdated. Evertune identifies these gaps so brands can strategically 'unblock' or feed data to the models.

Which markets does Evertune intend to disrupt?

Evertune positions itself as the evolution of three major categories: Search Engine Optimization (SEO), Brand Monitoring, and Search Advertising. By citing the total addressable market of these three sectors as over $400 billion, they suggest that 'LLM Optimization' will eventually capture a significant portion of traditional marketing budgets.

What is missing from this pitch deck?

The provided slides are heavily focused on the 'Why Now' and 'Product' sections. It lacks a team slide (crucial for a Seed round), a clear 'Ask' slide detailing how the $4M will be spent, a business model/pricing slide, and a forward-looking roadmap. These may have been in the 8 slides not included in the visual set but are notable omissions here.

Evertune pitch deck: the facts

Company

Evertune

Year

2024

Stage

Seed

Slides

17

Sector

Advertising, Data analytics, AI

Deck type

Full Pitch Deck

Outcome

$4M Raised

Headquarters

North America

Evertune pitch deck PDF

The full Evertune deck is embedded on this page and can be read slide by slide in the browser — no download or account required. Each slide is covered in the breakdown above.

What the Evertune pitch deck was used for

This is Evertune’s 2024 **seed-stage** pitch deck for a $4 million raise to build an AI-era brand analytics and marketing analytics platform that measures what LLMs and AI search say about brands and products[1][3][11]. The deck positions Evertune as a solution to the shift from traditional search to AI-powered discovery, helping advertisers understand and influence how AI systems recommend brands[1][2][3]. It was used as the primary fundraising narrative for the October 2024 seed round led by Eniac Ventures with participation from NextView Ventures and angel investor Roger Ehrenberg[1][3][4][11]. The slides highlight use cases such as measuring brand performance versus competitors and analyzing word associations that AI models make about specific brands, including a luxury SUV example from the deck text provided.

Business model: SaaS marketing analytics platform that measures and optimizes how AI search and LLMs describe, rank, and recommend brands across prompts and engines[1][2][3][12][13].

Round

Seed[1][3][5][8][9][11].

Raised

$4,000,000[1][3][4][5][8][9][11].

Lead investor

Eniac Ventures[1][3][4][5][9][11].

Investors

Eniac Ventures, NextView Ventures, Roger Ehrenberg[1][3][4][5][9][11].

Founded

2024[1][3][12][13].

Founders

Brian Stempeck, Poul Costinsky, Ed Chater[2].

Headquarters

New York, United States[1][5][8][13].

Industry

Marketing analytics, Advertising technology, AI brand analytics[1][2][3][12][13].

Year: 2024[1][3][4][5][8][9][11].

Total funding: $19 million in venture capital across a $4M seed round in 2024 and a $15M Series A in 2025[2][8][9][13][14].

Use of funds as presented: To build and commercialize a brand analytics and marketing analytics platform for the AI era, focused on measuring and optimizing how LLMs and AI search talk about and recommend brands, and to develop accompanying AI‑powered advertising capabilities[1][2][3][5][9][12][15].

What happened after the Evertune deck

The seed round this deck supported closed successfully in October 2024, enabling Evertune to launch its AI Brand Index and build out its AI visibility and GEO advertising platform[1][2][3][4][5][9][12][13]. The company subsequently raised a $15M Series A in August 2025, scaled revenue and headcount, and was acquired by Impact Tech in December 2025, with its AI search‑visibility measurement folded

• Raised a **$4M seed round** in October 2024, led by Eniac Ventures with participation from NextView Ventures and Roger E
• Launched commercially in late 2024 with the AI Brand Index, providing cross‑engine AI visibility measurement for brands
• Raised a **$15M Series A** in August 2025 led by Felicis Ventures, with participation from existing investors, bringing
• Expanded its platform into GEO‑based advertising capabilities, including placing brands on sources AI cites and retarget
• Achieved meaningful revenue and team growth by 2025 (e.g., later profiles cite around $3.4M in 2025 revenue and a team o
• Was acquired in December 2025 by Impact Tech, the company behind impact.com, integrating Evertune’s AI search‑visibility

What the Evertune deck got right

• Strong alignment with AI‑driven discovery macro trend. The company addresses a **clear, emerging pain point** for marketers: understanding and influencing how AI models and AI search recommend brands, at a time when discovery is shifting away from traditional search toward LLMs and social platforms, a trend reinforced by the Wall Street Journal coverage highlighted in the deck[1][2][3].
• Rigor and scale in AI visibility measurement. Evertune’s product is framed as a **statistics‑driven AI Brand Index**, later described as running 100,000+ prompts per report across many AI engines to yield statistically significant insights, which positions the platform as a rigorous measurement layer rather than anecdotal AI testing[2][9][12][13].
• Highly credible adtech founding team. The founding team consists of experienced adtech operators—Trade Desk veterans and Adbrain alumni including Brian Stempeck, Poul Costinsky, and Ed Chater—who previously scaled programmatic and identity products, a strong fit for building AI marketing analytics[2][3][12][13].
• Concrete, brand‑level use‑case illustration. The deck’s client example for luxury SUVs and word associations for Porsche shows how the product can **benchmark brands versus competitors and surface which messages cut through AI conversations**, making the value proposition tangible to investors and brands.
• High‑quality investor backing for the seed round. Institutional validation is strong for a seed‑stage company: the **$4M seed round led by Eniac Ventures with NextView Ventures and Roger Ehrenberg** indicates that experienced adtech and early‑stage investors bought into the thesis and the deck’s narrative[1][3][4][5][9][11].
• Integrated measurement‑to‑activation product vision. Evertune’s roadmap from analytics to **GEO‑based advertising**—placing brands on the sources AI cites and retargeting users after AI conversations—creates an integrated story of measurement feeding activation, which can support stronger monetization and strategic relevance to marketers[2][7][9][13][15].

What could have been stronger

• Limited quantified evidence on methodology in example slide. From the available OCR, the client example slide focuses on qualitative word associations (e.g., “hefty price tag,” “premium materials”) for Porsche SUVs but does not show quantified metrics such as index scores, share of AI recommendations, or statistical confidence intervals, which could leave investors uncertain about the rigor and repeatability of the measurement methodology relative to the later‑described AI Brand Index.
• Trend slide leans on press clipping rather than clear differentiation. The deck excerpt references a Wall Street Journal article about Google’s grip on search slipping as TikTok and AI startups challenge it, but based on the OCR text provided, the slide appears to be mostly a press clipping without clear data or a tightly articulated link to Evertune’s unique differentiation beyond the general trend that AI is changing discovery.
• Scale and multi‑engine coverage under‑communicated in visible slides. Given what external sources later emphasize about polling many AI systems and running 100,000+ prompts per report, the partial deck text we have does not yet show that scale or cross‑engine coverage; investors relying only on the deck text might not fully appreciate how broad and statistically grounded the measurement is, making the product initially look more like a single‑LLM analytics tool than a multi‑engine platform.
• Narrow initial use case illustration. The luxury SUV example is useful to make the concept concrete, but focusing on a high‑end consumer category may leave B2B or non‑luxury brand investors wondering how well the approach generalizes to their industries, especially without additional case studies or sectors shown in the OCR segment.
• Traction and early customer evidence not apparent in excerpted slides. The OCR shows the label “Private & Confidential,” but the visible slides do not include any explicit information about traction, paying customers, or usage metrics at the time of the seed round; external coverage mentions early work with agencies and brands, yet this evidence is not visible in the deck excerpts we have, which may weaken perceived traction in the deck itself.

How an investor would read this deck

What draws attention

• Positioning as a **statistics‑first measurement layer** for AI visibility and brand discovery across multiple AI engines, not just a single LLM, which directly addresses marketers’ emerging concern about how AI systems recommend brands[2][3][9][12][13].
• Founding team of former The Trade Desk leaders and Adbrain alumni (Brian Stempeck, Poul Costinsky, Ed Chater) with prior experience scaling adtech and data products, which is a strong signal for executing in marketing analytics and advertising technology[2][3].
• Demonstrated investor interest and validation: the **$4M seed round led by Eniac Ventures with NextView Ventures and Roger Ehrenberg** provides institutional backing and suggests the story in the deck resonated with experienced adtech investors[1][3][4][5][9][11].
• Macro tailwind slides anchored in credible external reporting (e.g., Wall Street Journal coverage of Google’s search grip slipping as TikTok and AI challengers emerge), which frame the shift to AI‑powered discovery as a large structural change in advertising and marketing[1].
• Clear use‑case in the deck showing brand benchmarking and word association analysis for luxury SUVs (e.g., Porsche vs. competitors), illustrating how Evertune can reveal which messages AI models pick up and repeat in consumer queries.

Risks that stand out

• Rapid evolution of LLMs and AI search surfaces could change APIs, content policies, and ranking behaviors frequently, potentially undermining the stability of Evertune’s measurement methodology and requiring constant adaptation to maintain accurate AI Brand Index reports[2][9][12][13].
• Large incumbent ad platforms or marketing analytics providers might add similar AI visibility measurement and activation capabilities, leveraging existing advertiser relationships and data to compete with or subsume Evertune’s offering, which could pressure pricing and differentiation[2][9][13].
• Dependence on external AI systems and search providers—if major LLMs restrict automated querying or metadata access, this could affect Evertune’s ability to run high‑volume prompts across many engines and maintain statistically robust reports[2][9][12][13].
• At the seed stage, the deck excerpts do not show significant proven revenue or a large installed base; later sources report growth and a Series A, but at the time of the deck, investors would have faced typical early‑stage execution risk in turning promising analytics into a scalable, repeatable com
• The GEO advertising component (placing ads on sources AI cites and retargeting AI researchers) introduces privacy, attribution, and measurement complexities that may be sensitive to evolving regulations and browser/platform policies, posing regulatory and technical risk to the long‑term activation s

Questions this deck invites

• How exactly is the **AI Brand Index** constructed—what prompts are run, which AI engines are included, how is sampling performed, and what statistical techniques are used to ensure significance and guard against LLM volatility and prompt se
• What were Evertune’s **commercial traction metrics at the time of the seed** (number of paying customers or pilots, revenue, retention, agency partnerships), beyond the qualitative examples shown in the deck and later anecdotes about workin
• How defensible is Evertune’s position as a measurement and activation layer for AI visibility—are there proprietary data assets, integrations, or IP that make it hard for large incumbents (e.g., major ad platforms or marketing clouds) to re
• What does the competitive landscape look like for **generative engine optimization (GEO)** and AI brand analytics, and how does Evertune differentiate both on measurement rigor (number of prompts, cross‑engine coverage) and on downstream ac
• How did Evertune plan to evolve from a pure analytics platform into a full GEO advertising capability (e.g., Ads Agent placing ads on sources AI cites and retargeting users after chats), and what were the milestones and risks associated wit

What founders can take from the Evertune deck

• A clear, timely **macro narrative**—such as the shift from traditional search to AI‑driven discovery, supported by major press like the Wall Street Journal—can effectively frame why a new analytics platform is needed and why the market is large and changing[1][2][3].
• Demonstrating **how AI models talk about real brands** with concrete examples (e.g., luxury SUV preferences and Porsche word associations) makes an abstract AI analytics concept tangible for investors, helping them picture use cases for their portfolio companies or potential customers.
• Highlighting the founding team’s **domain experience in adtech and marketing analytics** (Trade Desk veterans and Adbrain alumni) can materially strengthen credibility for a complex, data‑heavy product, especially when the company is pre‑scale[2][3].
• Articulating a product that spans both **measurement and activation**—from the AI Brand Index to GEO‑based advertising that places brands in AI‑cited sources and retargets AI researchers—can position a startup as an essential layer in a new marketing stack rather than a standalone tool[2][7][9][13][
• Using the deck as part of a coordinated launch (stealth exit, investor blog posts, media coverage, and a detailed pitch deck) can help seed‑stage companies secure funding while simultaneously educating the market on a new category like AI brand visibility and generative engine optimization[1][3][4][
• Maintaining **statistical rigor and transparency** in describing methodologies (number of prompts, engines covered, confidence levels) is critical for analytics products; later public materials emphasize this for Evertune, suggesting that future decks should foreground such details even more than th

Evertune pitch deck: common questions

What does Evertune do?

Evertune is a marketing and **brand analytics platform for the AI era** that measures how large language models and AI search platforms talk about, rank, and recommend brands, then turns that visibility data into actionable insights and ad activation[1][2][3][12][13][15]. Its core product, often described as the **AI Brand Index**, runs large numbers of prompts across many AI systems (e.g., ChatGPT, Gemini, Claude, AI Overviews, Copilot, Perplexity, Meta AI, DeepSeek) to produce statistically significant scores and diagnostics on brand visibility and messaging effectiveness[2][9][12][13].

How much did Evertune raise in its seed round and who invested?

In October 2024, Evertune raised a **$4 million seed round** after emerging from stealth[1][3][4][5][8][9][11]. The round was **led by Eniac Ventures**, with participation from **NextView Ventures** and angel investor **Roger Ehrenberg**[1][3][4][11]. Public fundraise tracking sites and firm blogs consistently characterize this round as a seed financing for Evertune’s AI brand analytics and marketing analytics platform[1][3][5][8][9].

Did the fundraise described in this pitch deck actually close, and when?

Yes. The seed round described in this pitch deck closed as a **$4M seed financing in October 2024**, led by Eniac Ventures with NextView Ventures and Roger Ehrenberg participating[1][3][4][5][9][11]. Subsequent reporting and investor write‑ups confirm that this was the company’s initial institutional round and that the deck was used to support that raise[1][3][4][11].

Who founded Evertune and what is their background?

According to Evertune’s and investors’ public materials, the company was **founded in 2024** by early members of The Trade Desk, including **CEO Brian Stempeck** and co‑founders **Poul Costinsky** and **Ed Chater**, who previously joined The Trade Desk via its acquisition of Adbrain[2][3][12][13]. The founding team’s background is in adtech, programmatic advertising, and cross‑device identity graphs, which the deck and later coverage highlight as relevant experience for building AI‑driven marketing analytics[2][3].

How does Evertune’s product work in relation to AI and LLMs?

Later profiles and product pages describe Evertune’s platform as analyzing prompts and responses at scale across major LLMs and AI search surfaces, then turning that into both **measurement** (the AI Brand Index) and **activation** (e.g., ad placement on sources AI cites, retargeting users after AI chats)[2][7][9][12][13][15]. While the deck OCR we have shows a specific example for luxury SUVs and word associations for Porsche, external sources confirm that these are illustrative of the platform’s broader capability to benchmark brands versus competitors and extract which messages cut through AI conversations[1][2][3][9][12][13].

Sources

Funding and outcome facts on this page were researched on 2026-08-30 from the pages below.

• Pitch Deck : AI Ad Analytics Startup Evertune's $4 Million Seed Round
• Meet Evertune, A Gen-AI Analytics Startup Founded By Trade Desk ...
• Why We at NextView Ventures Are Investing in Evertune
• Brian Stempeck's Post - LinkedIn
• Evertune announced it raised $4 Million in an initial filing from an offering of $4 Million
• AI is Rewriting Discovery. Are You Ready? - Apple Podcasts
• Evertune — Own the AI customer journey
• Evertune: Funding, Team & Investors | Startup Intros

Evertune pitch deck slides

What each slide of the Evertune pitch deck says

Slide 2

Search is going through a massive change best tv for movies xX $$ @Q EE SmetTV Under$S00 4K Underddinches 43-SSinches 55-éSinches About 4870,00.000 rests (054 seconds) Howden ay metas? (5 According to Game Rant, the Samsung S95C QD-OLED 55' TV is the best overall TV for movies, while the LG C2 Series 48-Inch Class OLED EVO TV is the best entry-level TV for movies. Other TVs that are good for movies include: + Sony OLED 65-inch BRAVIA ABOL TV: Best OLED TV for movies + SAMSUNG 75-inch Class Neo QN8SB 4K TV: Best 4K TV for movies + LGG3 65 Inch OLED EVO TV: Best high-end TV for movies @) Fe EEE; Private & Confidential 2

Slide 3

Google now has competition — Al-powered search is gaining scale © OpenAl if) perplexity ~~ ANTHROP\C 200m Weekly Unique Users 50m Unique Users 5m Unique Users Linked ff} 160m Weekly Unique Users Eee Private & Confidential 3

Slide 4

THE WALL STREET JOURNAL. Google's Grip on Search Slips as TikTok and Al Startup Mount Challenge A flurry of new offerings for advertisers is hitting the market https://www.wsj.com/tech/online-ad-market-google-tiktok-9599d7e8?mod=mhp evertune Private & Confidential 4

Slide 5

Pe ? The future of Al search won't just live on Google.com (© Ask Meta Al or Search ol BEST © © [ 4 BUYa oi. lo} er = Best Buy Chatbot ; iii EiEhemyomen, Co ss Shopping ors Home Thester or err te sisas ooOGoDons Picking out the right product a — Rost move a 03 0000000 ©) can be hard, but our experts are por =] 5 i do i er Seer In order for me to get you to the br mk ripper Tass right person, could you let me sm — know what you are shopping tits oo as oom diately for? : 2 Le TV & audio vetine: Private & Confidential 5

Slide 6

Brands need to know what LLMs are telling consumers, and how to help Al learn about their products.

Slide 10

Client Example: Understanding Consumer Preferences for Luxury SUVs Consumer Preferences for Luxury SUVs See how well a brand performs vs. competition across key product features and attributes = Porsche == Mercedes == Volvo = BMW Reliability Exclusivity evertune Word Association for Porsche SUVs See what words Al models most associate with the brand brands to see what messages are cutting through hefty price tag premium materials high-quality materials premium price tag driving dynamics Porsche Cayenne luxury SUV market " driver-centric de51gn turbocharged V6°J orsche Mac highperformance sportsacars intuitive infotainment system g powerful engine options sharp handling advanced technology f…

Slide text above is read directly from the Evertune deck PDF embedded on this page.

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