The GEO and AI-visibility tooling market in 2026: vendors, funding, and how to read the landscape

The AI-visibility tooling market in 2026 is a crowded, well-funded category (100+ tools, $200M+ raised), led at the enterprise end by Profound, a $1B unicorn, with Ahrefs Brand Radar and the Adobe-acquired Semrush bringing search-data scale, and a wave of funded challengers (Bluefish, Peec, Scrunch, AthenaHQ) filling in the middle.

Disclosure: [GrackerAI](https://gracker.ai/) is the author's own AI-visibility and media-intelligence company. It is one of many entrants in the category described here, and this guide treats it and every other vendor neutrally.

How big and how crowded the category is

Two years ago, tracking whether an AI answer mentioned your brand was a manual exercise: paste a prompt into ChatGPT, read the response, repeat. By 2026 it is an industry. Independent counts put the field at 100+ competing AI-visibility tools with more than $200M in venture funding flowing into the space, and roughly 20+ dedicated platforms (as opposed to bolt-on modules) built specifically to measure generative-engine and answer-engine visibility.

Pricing has settled into a wide band. The industry-average price is around $337 per month, but that average hides a spread from free graders and ~$29/mo entry tools up to enterprise contracts that run into five figures annually. The average is a useful anchor, not a quote; where a vendor sits in that band tells you more about its intended buyer than about its quality.

Market-size projections should be read with care. One analyst model (treat this as a vendor/analyst estimate, not a settled figure) pegs the GEO services market at $1.48B in 2026 growing to $17.02B by 2034, a 45.5% CAGR. Numbers that large, that far out, in a category this young, are directional at best. The useful signal is not the decimal places; it is that serious capital and serious analysts now treat AI visibility as its own line item rather than a footnote under SEO.

For the dated capital data behind the funding figures below, see the investor landscape. For scored, side-by-side profiles of the platforms, see the vendor matrix.

The enterprise leaders

At the top of the market, one name recurs in nearly every buyer conversation: Profound, a New York company that has become the reference point for enterprise AI visibility.

Its funding history is unusually fast. In August 2025 it raised a $35M Series B led by Sequoia Capital (with Kleiner Perkins, Khosla Ventures, Saga VC, and South Park Commons), bringing its total to $58.5M at the time. Six months later, in February 2026, it raised a $96M Series C at a $1B valuation, led by Lightspeed Venture Partners (with Sequoia, Kleiner Perkins, Evantic Capital, Saga VC, and South Park Commons returning). That crossed it into unicorn territory and brought total funding to $155M.

Its client roster reads like a who's-who of enterprises worried about disappearing from AI answers: a Fortune 10 company plus Ramp, U.S. Bank, Indeed, MongoDB, Docusign, and Chime. The technical differentiator buyers cite most is Prompt Volumes, a panel-data product. Rather than only running synthetic prompts, Profound licenses real conversations from double-opt-in consumer panels, hundreds of millions of prompts per month, GDPR- and CCPA-scrubbed. That gives it a view of what people actually ask AI assistants, not just what a vendor guesses they might ask. For enterprises trying to prioritize which prompts matter, that panel view is the pitch.

The search-data incumbents entering

The second force in the market is the established SEO-data players, who already own enormous prompt and query datasets and are extending them into AI visibility.

Ahrefs Brand Radar is the most notable because Ahrefs is bootstrapped, with no venture capital, which is rare in this list. It launched in beta around March 2025, shipped Brand Radar 2.0 in August 2025, and added custom AI-prompt tracking in January 2026. It models 405M+ search-backed prompts and is widely regarded as having the best data scale and the best coverage of Google's AI Mode, which many pure-play monitors handle poorly. Pricing reflects the depth: the all-platform bundle runs around $699/mo on top of a base plan starting at $129+/mo (review and pricing).

Semrush is the more consequential story for the category's structure. Its AI Visibility Toolkit draws on 261M+ LLM prompts and prices at roughly $99/domain/mo as an add-on. But Semrush is now Adobe-owned: Adobe announced a ~$1.9B all-cash acquisition ($12.00/share) on November 19, 2025 and completed it on April 28, 2026. Adobe's stated rationale, per its own release and contemporary coverage, is brand visibility, GEO, SEO, and what it calls "agentic search optimization." When a company the size of Adobe pays nearly $2B partly for a GEO capability, the category's legitimacy is no longer in question.

Behind these two, the legacy enterprise SEO platforms, BrightEdge and Conductor, are adding AI-visibility modules to their existing suites, as are seoClarity, Yext, and Botify. These are less about a new dataset and more about keeping existing enterprise contracts inside one dashboard.

The funded pure-play challengers

Between the enterprise leader and the incumbents sits the most active segment: venture-funded startups built exclusively for AI visibility.

Bluefish AI is the best-capitalized challenger. It raised a $20M Series A led by NEA in August 2025 (with Salesforce Ventures, Crane Venture Partners, Swift Ventures, and Bloomberg Beta), then a $43M Series B in April 2026, bringing its total to $68M. It targets Fortune 500 buyers, with customers including Adidas, Amex, Hearst, and Ulta.

Peec AI raised about $21M in a Series A (some sources cite ~$29M; use the conservative figure) and serves the mid-market, reporting 1,500+ marketing teams including Wix, ElevenLabs, and Chanel, with a Starter plan around $95/mo.

Scrunch AI has been operating since 2023, has raised about $19M, covers ChatGPT, Perplexity, and DeepSeek, and reports 500+ brands.

AthenaHQ (Athena) is Y Combinator-backed and enterprise-focused, with customers including ZoomInfo, SoFi, and Volkswagen (athenahq.ai). Evertune is cited among the best-funded, having raised $20M+.

Daydream is a useful reminder that not every entrant is a dashboard. It is an AI-native SEO/AEO agency, not just a tool, and raised a $15M Series A in April 2026 led by WndrCo with First Round Capital and Basis Set, for a total of $21M. The distinction matters when you segment the market: some of this capital is buying software, and some is buying a service model.

The accessible / entry tier

Not everyone needs a $700/mo bundle or an enterprise contract. A growing tier serves smaller teams and first-time buyers.

• Otterly.AI starts around $29/mo, one of the lowest paid entry points.
• HubSpot ships a free AEO Grader, a low-commitment way to get a first read on AI visibility.
• Rankshift tracks 8 engines (ChatGPT, Gemini, Perplexity, Claude, AI Overviews, AI Mode, Mistral, Llama), with a Starter plan at EUR69/mo and Pro at EUR159/mo.
• Goodie AI tracks visibility across ChatGPT, Gemini, Claude, Perplexity, AI Overviews, AI Mode, Grok, Meta AI, and Copilot, and published an "AEO Periodic Table" built on 1M+ prompts.
• Knowatoa focuses on brand-accuracy and sentiment monitoring rather than pure presence tracking.

This tier is where most teams should start if they have never measured AI visibility at all. A free grader plus one low-cost monitor answers the first question (are we present, and roughly where) before anyone signs an enterprise contract.

How to read the landscape as a buyer

The category looks chaotic because it mixes very different products under one label. Segment before you shortlist:

• Data source and scale. Panel data (Profound), search-backed prompt models (Ahrefs' 405M+, Semrush's 261M+), or synthetic prompts you configure yourself. Bigger and more real is generally better, but only for the prompts your buyers actually use.
• Engine coverage. Confirm coverage of the engines your audience uses, and check Google AI Mode specifically, since it is the weakest spot for many monitors and a strength for Ahrefs.
• Price tier. Free grader, ~$29 to ~$99/mo entry, mid-market, or enterprise. Match the tier to the decision you are trying to make, not to the vendor's marketing.
• Monitoring tool vs workflow/agency. A dashboard tells you where you stand; an agency model like Daydream, or a workflow tool, is meant to move the number. These are not interchangeable purchases.

For a structured walkthrough of how to weigh these axes against your own use case, see choosing an AI visibility tool. To connect the tool choice to the metrics themselves, see measuring AI visibility, and to plan what to do once you can measure, the AEO/GEO experimentation roadmap.

What the funding wave signals

Three things follow from the capital flowing into this category.

First, consolidation has started. Adobe buying Semrush for ~$1.9B is the clearest signal: incumbents with distribution will acquire rather than build, and more of the pure-plays will be absorbed into larger marketing suites over the next cycle.

Second, the category is maturing. A $1B unicorn (Profound), a bootstrapped incumbent with a 405M-prompt model (Ahrefs), and multiple funded challengers do not coexist in a fad. AI visibility is becoming a durable line item, which is why analysts now model it separately even if their long-range numbers are estimates.

Third, the market is splitting into an enterprise tier and an accessible tier, with the middle contested by funded challengers. Where you land depends less on which vendor is "best" in the abstract and more on which segment matches your budget, your engine mix, and whether you want to measure the problem or hire someone to fix it.

For the dated capital history behind every figure here, and scored profiles of the platforms, work from the investor landscape and the vendor matrix alongside the annual read in the state of AI search 2026.

Key vendors at a glance

The table is a starting shortlist, not a ranking. The right pick is the one whose data source, engine coverage, price tier, and tool-vs-service model match the specific question you are trying to answer.