From £3m Pre-Seed Backing to Early Revenue Traction, the London Venture Is Betting on Answer Engine Optimization as AI Rewrites the Rules of Digital Visibility.
A newly launched artificial intelligence start-up has reached $1 million in annualized revenue in less than 90 days after opening its platform to customers, highlighting the rapid rise of a potential new frontier in digital marketing: Answer Engine Optimization.
Founded in 2025, Searchable, a London-based AI software company, is positioning itself at the forefront of what its founders describe as the next phase of online visibility. Rather than focusing solely on traditional search engine rankings, the company develops tools designed to help brands understand how they appear in responses generated by large language models and AI-powered search systems.
At a time when conversational AI platforms are rapidly reshaping how users access information, Searchable argues that organisations must adapt to a new environment in which answers, not links, increasingly define digital presence.
For more than two decades, search engine optimization (SEO) has been the cornerstone of digital marketing strategy. But the rise of generative AI systems capable of producing direct, conversational responses has introduced a fundamental change. Increasingly, users ask questions in natural language and receive synthesized answers drawn from vast data corpora rather than navigating through ranked lists of web pages.
Searchable’s core proposition is that this shift demands a new discipline, and that would be Answer Engine Optimization (AEO). The company’s software aims to monitor how brands, products, and websites are referenced across AI-generated responses, and to provide analytics that help organisations improve their representation.
The platform tracks visibility across multiple large language model (LLM) systems and AI search interfaces, offering insights into sentiment, citation patterns, and contextual positioning. This is translated into actionable strategies via the platform’s ‘agent’, which advises brands on the next steps necessary to grow their presence and add more revenue streams to their business. In practical terms, this means companies can see not only whether they are mentioned, but how they are described, and in comparison, to whom. These conversations surface unique insights and commercial opportunities which brands are then advised to capitalize on.
Industry analysts suggest that the stakes are significant. As AI systems become intermediaries between consumers and information, being accurately and favourably represented in generated responses could become as critical as ranking highly on conventional search engines once was.
Founders Blend Marketing and AI Expertise
Searchable was established by three co-founders who combined backgrounds in digital marketing and artificial intelligence engineering.
Chris Donnelly, a serial entrepreneur, previously founded and exited companies in the marketing and health technology sectors. Beyond Searchable, he owns The Creator Accelerator and co-owns SayWhat, a data analytics firm that processes millions of online posts weekly to identify trends and consumer sentiment. He also founded Lottie, a health-tech start up, that boasts two major U.S. VC firms as backers.
Joining him are Arya Nagabhyru and Sam Hogan, both experienced AI engineers with prior involvement in AI agent start-ups. Their technical expertise underpins the development of Searchable’s monitoring and analytics infrastructure, designed to operate across rapidly evolving AI ecosystems.
The trio contends that effective AEO requires a fusion of marketing insight and technical fluency, and the ability to understand both how AI models process information and how brands craft narratives.
Beta Launch?
In November 2025, Searchable quietly introduced an invite-only beta version of its platform. Access was initially restricted to a limited group of customers, including several global brands, according to company statements.
Within 10 days of opening the beta, the company had generated $10K monthly recurring revenue (MRR). This drew attention within London’s start-up community, where rapid revenue traction is often viewed as a marker of product-market fit.
The announcement positioned Searchable as an early commercial contender in the nascent AEO sector. Observers noted that the promise of helping brands maintain visibility within AI-generated answers, particularly as traditional search referral traffic faces disruption, may explain the swift uptake.
Digital marketing executives interviewed following the launch described growing concern that AI chat interfaces could bypass websites entirely, delivering information directly within conversational responses. Tools that offer clarity into how those answers are constructed, they said, could become essential.
Momentum continued in December 2025, when Searchable announced it had secured approximately £3 million (around US$4 million) in funding. The pre-seed round was led by the UK-based venture capital firm Freestyle VC.
The investment valued the company at roughly $40 million, a substantial figure for a firm less than a year old. According to statements at the time, the capital would be used to accelerate product development, expand engineering and marketing teams, and support customer acquisition.
Freestyle VC cited the accelerating adoption of generative AI across industries as a key factor in its decision to back the start-up. Investors have increasingly sought exposure to companies building infrastructure and analytics around AI systems, rather than solely those developing foundation models themselves.
The funding round also reflected a broader trend in European technology markets, where AI-focused ventures have continued to attract capital despite wider funding slowdowns in other sectors.
Searchable’s emergence comes in an intensifying debate over how AI systems source and present information. As LLMs synthesise data from vast online corpora, questions around attribution, transparency, and bias have grown more prominent.
In this context, AEO represents both a commercial opportunity and a conceptual shift. Rather than attempting to “game” algorithms in the traditional SEO sense, AEO practitioners argue that optimisation must focus on clarity, authority, and structured information that AI systems can reliably interpret.
