Generative search is reshaping how users discover brands. Instead of clicking through ten blue links, users now ask questions directly to AI engines like ChatGPT, Gemini, Claude, and Perplexity, and expect compiled answers. These AI-generated responses are often the first, and sometimes the only way users see a brand, shaping awareness and trust before they ever visit a website.

This shift has led to Generative Engine Optimization, which focuses on making sure your brand, content, and expertise appear clearly and accurately in AI-generated answers. As AI systems pull information from many sources, brands now need to compete not only for search rankings, but for visibility inside AI responses. 

Below is a selected list of platforms designed to help marketers understand, measure, and improve performance in AI-driven discovery environments.

1. Similarweb Gen-AI Intelligence

Similarweb’s Gen-AI Intelligence is built around two complementary capabilities: AI Brand Visibility and the AI Traffic Tracker, together helping teams understand both presence and performance across generative AI platforms.

The AI Brand Visibility tool analyzes how brands appear in AI-generated responses by examining prompts, citations, and sentiment. It shows which questions and intents mention a brand, how often the brand is mentioned relative to competitors, which sources AI engines rely on when citing information, and how brands are positioned within AI answers. Sentiment analysis adds another layer by revealing how AI describes a brand, not just whether it appears.

The AI Traffic Tracker connects this visibility to real user behavior, measuring referral traffic from generative AI platforms to brand websites. This allows teams to identify which AI engines and prompts actually drive visits, helping separate high-level AI mentions from exposure that leads to measurable demand.

Together, these tools enable marketers to move beyond observing AI mentions and toward understanding which AI visibility actually matters, making generative search a measurable and optimizable channel.

Best for: SEO and marketing teams focused on measuring AI brand visibility and AI-driven demand.

2. Ahrefs Brand Radar

Ahrefs Brand Radar extends traditional brand monitoring into generative AI environments, allowing teams to track when, where, and how often brands appear in AI-generated answers. Its strength lies in competitive analysis, helping SEOs understand brand visibility relative to key competitors across topics and queries.

The tool enables teams to monitor visibility trends over time, making it easier to spot gains or losses in AI exposure as generative search evolves. While Ahrefs is best known for backlinks and keyword intelligence, Brand Radar repurposes that analytical foundation to focus on brand mentions and comparative presence within AI responses rather than classic SERPs.

Best for: SEO teams already using Ahrefs who want brand-level visibility insights in AI responses.

3. Otterly AI

Otterly AI is purpose-built to track brand mentions in AI-generated answers, with a focus on clarity and ease of use. It helps teams see whether their brand appears for specific prompts and how consistently it shows up across different AI platforms.

Rather than offering deep analytics, Otterly AI prioritizes monitoring and alerts, enabling users to quickly notice changes in AI visibility without extensive setup or interpretation. This makes it well suited for teams that want awareness and tracking without complex reporting.

Best for: Small to mid-size teams looking for lightweight AI brand monitoring.

4. AthenaHQ

AthenaHQ approaches GEO through the lens of content optimization for AI systems. Instead of focusing primarily on brand mentions, it helps teams evaluate how well their content aligns with the structures, entities, and answer formats favored by generative engines.

The platform emphasizes content readiness, offering insight into how pages may perform in AI-generated summaries, recommendations, and answers. This makes AthenaHQ particularly useful for teams focused on improving how existing or new content is interpreted and mentioned by AI.

Best for: Content and SEO teams optimizing articles for AI answer inclusion.

5. Goodie AI

Goodie AI focuses on understanding brand presence and framing within conversational AI outputs. It helps teams see whether brands are mentioned in AI responses and how they are described, including whether mentions are neutral, positive, or missing altogether.

Positioned as an entry-level GEO solution, Goodie AI emphasizes discovery and monitoring rather than performance measurement or attribution. It provides an accessible way for marketers to begin tracking AI visibility without deep technical requirements.

Best for: Marketers exploring AI visibility tracking for the first time.

6. Peec AI

Peec AI centers on tracking brand exposure and competitive presence across generative AI platforms. It helps teams understand how frequently brands appear in AI responses, the context of those mentions, and which competitors appear alongside them.

Its primary value lies in visibility benchmarking, allowing teams to compare AI presence across brands and categories. Peec AI is less focused on content optimization or traffic measurement, and more on understanding relative exposure.

Best for: Teams focused on competitive AI presence analysis.

7. Rankscale

Rankscale translates familiar SEO ranking concepts into the world of generative search. Instead of tracking keyword positions in SERPs, it measures how brands perform within AI-generated answers for defined queries.

This ranking-style approach makes it easier for SEO professionals to adapt existing workflows and reporting models to AI search, providing a more intuitive bridge between traditional SEO metrics and generative visibility.

Best for: SEOs looking for familiar ranking-style metrics applied to AI search.

8. Scrunch

Scrunch focuses on how AI systems understand and describe brands, rather than how often brands are mentioned. It helps teams identify gaps between intended brand messaging and the way AI-generated answers portray products or services.

The platform is often used to diagnose inconsistencies in AI-generated brand narratives, making it especially valuable for teams concerned with brand accuracy, tone, and perception across AI platforms.

Best for: Brand and communications teams concerned with AI perception.

9. Semrush AI Visibility

Semrush AI Visibility extends Semrush’s established SEO tooling into generative AI environments. It allows teams to analyze how brands and domains appear in AI-generated answers, building on existing Semrush data and workflows.

For organizations already using Semrush, this tool offers a low-friction entry into GEO, enabling AI visibility tracking without adopting an entirely new platform.

Best for: Semrush users expanding into AI search monitoring.

10. Profound

Profound is focused on understanding how AI engines interpret, prioritize, and assemble information. It aims to mention which sources, entities, and signals influence AI-generated responses across topics and categories.

Rather than supporting day-to-day SEO execution, Profound is positioned for strategic and research-oriented analysis, helping teams better understand the mechanics behind AI-driven discovery.

Best for: Strategy teams researching AI discovery dynamics.

My Personal Take on Working With These GEO Tools

After reviewing and working with a range of GEO platforms, one thing became clear: most tools do one part of the job well, but very few cover the full GEO picture.

Tools like Otterly AI, Goodie AI, and Peec AI are useful for answering a foundational question: does my brand appear in AI answers, and where? I liked how easy they are to get started with, especially for teams new to generative search. However, once you move past basic monitoring, they can feel limiting, particularly when trying to understand competitive context or business impact.

AthenaHQ and Rankscale stood out when it came to structure and familiarity. AthenaHQ is strong on the content side, helping teams think about how pages should be shaped for AI answers, while Rankscale makes the transition to AI search easier for SEOs by adapting ranking-style thinking. What I missed with both was a deeper connection between visibility and real-world outcomes.

Scrunch offered a different and valuable angle by focusing on how brands are described by AI, not just whether they appear. That perspective is especially helpful for brand and communications teams, though it’s less suited for tracking ongoing visibility trends or performance.

Tools like Ahrefs Brand Radar and Semrush AI Visibility felt most natural if you’re already embedded in those ecosystems. I liked the familiarity and competitive benchmarking, but they felt more like extensions of traditional SEO platforms than fully native GEO solutions.

Similarweb’s Gen-AI Intelligence was the most complete experience overall. What stood out was the ability to combine AI Brand Visibility with AI Traffic Tracking in one place. Instead of stopping at mentions or rankings, it made it possible to understand which prompts, citations, and AI platforms actually drive traffic and demand. That connection between visibility, competition, sentiment, and measurable impact is what makes it feel less like an experimental GEO tool and more like a platform teams can rely on long-term.

Choosing the Right GEO Tool for Your Brand

Generative Engine Optimization is still changing, but one thing is already clear: visibility in AI-generated answers is becoming as critical as rankings in traditional search.

The right GEO tool depends on how deeply you need to understand that visibility. While some teams may only need basic monitoring or content guidance, others require a clearer view of which AI exposure actually drives engagement and demand.

As AI continues to influence buyer journeys, investing in GEO capabilities that connect visibility with real impact will be key to staying competitive.

FAQs

1. What is Generative Engine Optimization (GEO)?

GEO is the practice of optimizing content and brand presence for AI-generated answers rather than traditional search result pages.

2. What is the best GEO tool?

Similarweb’s Gen-AI Intelligence is the most comprehensive GEO tool, combining AI Brand Visibility and AI Traffic Tracking to show how brands appear in AI answers and which exposure drives real demand.

3. How is GEO different from SEO?

SEO targets rankings and clicks in search engines, while GEO focuses on visibility, citations, and representation within AI-generated responses.

4. Can AI visibility be measured accurately?

Yes, but measurement varies. Some tools track mentions and sentiment, while others (like Similarweb) connect AI exposure to actual traffic.

5. Do AI engines send traffic to websites?

In some cases, yes. Certain AI platforms cite sources or link to websites, making traffic attribution increasingly important.

6. Are GEO tools replacing SEO tools?

No. GEO tools complement SEO by addressing a new discovery layer rather than replacing traditional optimization.

7. Which teams should care about GEO?

SEO, content, brand, and growth teams all benefit from understanding AI-driven discovery.

8. Is GEO relevant for B2B companies?

Absolutely. AI engines are frequently used for research, comparisons, and vendor discovery in B2B contexts.

9. Is it too early to invest in GEO?

While the space is young, early adoption helps brands shape how AI systems understand and reference them over time.