AI Search Visibility: Peec doubles to $10M in a few months

The history of silent but significant growth

Peec was born in Berlin with an apparently niche idea: to measure how often — and in what way — brands are mentioned in AI-generated responses. However, the market has responded surprisingly. According to sources cited by TechCrunch , the startup has more than doubled its annualized revenue in just a few months, surpassing the $10 million mark.

This growth pace is no accident. In fact, it coincides with the rapid spread of tools like ChatGPT, Perplexity, Google AI Overviews, and Microsoft Copilot. These systems no longer return a list of links: they generate direct answers, selectively citing sources and brands. Consequently, a company's visibility no longer depends solely on its ranking on Google, but also on how often language models mention it.

Peec has identified this need before it became mainstream. Therefore, its trajectory tells us something bigger than a single startup: it tells us about a structural change in how consumers and B2B buyers search for information.

Winners and losers in the new AI search ecosystem

Who profits from Peec's growth? First of all, brands that have already invested in authoritative, structured, and citable content. Language models tend to favor sources that appear reliable, up-to-date, and well-organized. Therefore, companies with a solid editorial presence — blogs, white papers, detailed product pages — start with an advantage.

On the flip side, small and medium enterprises that have neglected digital content creation are in a tough spot. Not because they're being actively penalized, but simply because they don't exist in the data pool AI models use to build their answers. This is about being invisible, not penalized.

Among potential losers are also SEO agencies and professionals who continue to measure success solely through traditional metrics: Google rankings, organic traffic, CTR. These metrics remain relevant, but they are insufficient. Similar to what happened with the shift from desktop to mobile, those who don't update their measurement tools risk optimizing for a channel that weighs less and less.

Finally, winners also include platforms that — like Peec — offer dedicated monitoring tools for AI search. The fact that a European startup reached $10 million in ARR in this segment suggests that demand is real and growing fast.

SHM Studio's take: what's really changing

We at SHM Studio we've been observing this phenomenon closely for several months. Peec's growth confirms a thesis we've long supported: optimization for AI search — often called Answer Engine Optimization o AEO — it's not a passing fad. It's an emerging discipline with solid foundations.

However, it's important not to panic or overreact. Traditional SEO isn't dead. Plus, Google is still the main starting point for most commercial searches in Italy. It's not about replacing one strategy with the other, but rather blending them smoothly.

What changes is the logic of visibility. In the past, it was enough to appear on the first page of search results. Today, you also need to be cited in the answers generated by AI. Therefore, content quality — its depth, structure, and authority — becomes even more crucial. Language models don't cite pages optimized for keywords: they cite sources that thoroughly answer specific questions.

According to research by Gartner , the volume of traditional searches could significantly decrease by 2027-2028 due to the spread of AI chatbots. This data should not be interpreted as a catastrophe, but as a signal of user attention reallocation.

The work still in progress: what's missing from current tools

Peec's growth is impressive, but the AI search monitoring market is still under construction. Therefore, it is useful to understand what these tools can do today and what they still cannot measure accurately.

Currently, monitoring platforms like Peec track the frequency of brand mentions in AI responses, the associated sentiment, and comparatively cited competitors. These are useful but partial metrics. In fact, there isn't yet a shared standard for measuring the impact of AI mentions on real conversions. The link between visibility in AI search and revenue remains difficult to quantify.

On top of that, language models update their knowledge base behind the scenes. So, a brand could rank great today and lose visibility tomorrow without getting any warning signs. This lack of transparency is one of the biggest hurdles the industry still has to figure out.

As highlighted by Harvard Business Review , trust in AI-generated content largely depends on the quality of the underlying sources. For this reason, investing in authoritative content is the most robust long-term strategy, regardless of the monitoring tools used.

Operational implications for Italian B2B and retail SMEs

What should an Italian SME concretely do in the face of these changes? The answer is not to immediately buy an AI search monitoring tool. First of all, you need to build the right foundations.

The first step is an audit of existing content. Do the website pages comprehensively answer the questions that buyers typically ask? Are they structured so that a language model can extract clear information from them? If the answer is no, the problem is not the lack of a monitoring tool: it's the lack of quotable content. Our team of SEO copywriting works exactly on this level.

Subsequently, it is appropriate to strengthen the presence on sources that AI models tend to favor: Wikipedia, authoritative industry sites, indexed press releases, mentions in recognized digital media. This process is often called digital PR and integrates naturally with a strategy SEO well-structured.

Moreover, for B2B companies, LinkedIn represents an increasingly relevant channel. Some AI models draw on public LinkedIn content to build answers about companies and professionals. Therefore, an active and consistent presence on the platform — through LinkedIn campaigns e organic content — indirectly contributes to visibility in AI search.

Finally, for retail SMEs, the product sheet remains the fundamental unit. Detailed descriptions, complete technical specifications, verified reviews: these are all elements that language models use to build answers to purchase queries. A site Web optimized in this direction is the foundation of any future visibility strategy.

Next moves: three concrete priorities for the second half of 2026

Peec's growth indicates that the market is moving rapidly. However, it is neither necessary nor advisable to react with disorganized urgency. There are three priorities that Italian SMEs can address in a structured way in the coming months.

The top priority is mapping AI queries relevant to your industry. What questions do potential customers ask ChatGPT or Perplexity before buying? How does the AI answer these questions? Does the brand appear in the answers? This analysis can be done even without dedicated tools, simply by manually testing the most common queries. The team at AI strategy by SHM Studio supports companies in this exploratory phase.

The second priority is the production of structured content. In-depth articles, detailed FAQs, industry guides: these are the formats that AI models cite most frequently. A strategy of Digital marketing that integrates these formats increases both traditional organic traffic and visibility in AI search.

The third priority is gradual monitoring. You don't need to jump right into a tool like Peec. Still, it's a good idea to start tracking brand mentions in AI answers manually, at least once a month. This builds a data baseline that will come in handy when you decide to use more advanced tools.

To delve deeper into these topics or request an assessment of your digital presence, you can contact the SHM Studio team . Furthermore, additional resources and updates are available on our Blog . The google ads campaigns remain an effective complementary tool for maintaining visibility during the transition to new search paradigms.