Signal AI launches Risk Scanner to turn static risk registers into real-time early warning systems. LONDON / NEW YORK - June 18, 2026 - Signal AI, a global leader in AI-driven decision intelligence, today announced the launch of Risk Scanner, a pioneering capability designed to shift enterprise risk management from reactive tracking to proactive crisis preemption through real-time early warnings. Unlike generalized risk register management tools, Risk Scanner enables organizations to upload their unique registry of key risks and use Signal AI's vast global data engine to automatically detect the earliest "weak signals" of, for example, regulatory, supply chain, and reputational disruption. This new approach to risk register monitoring gives leadership teams the critical runway they need to act. As the external threat landscape becomes more volatile, risk and compliance teams struggle to continuously monitor how shifting global events impact their specific corporate risk profiles. Risk Scanner bridges this gap by directly connecting an organization's internal risk register to real-world global data, transforming theoretical risk management into a proactive, data-validated system. "The most important thing for risk teams today to understand is not just what's happening currently, but to proactively see what lies ahead," says David Benigson, CEO and co-founder of Signal AI. "Signal AI's ability to detect anomalies in the data, in real-time, is a genuine advantage for risk teams to spot not just known enterprise risks, but the unknowns. This new tool means tracking emerging risks in a matter of minutes, not months." Risk Scanner eliminates reactive monitoring by automating how companies detect the earliest signs of emerging threats across their specific risk profiles: * Upload Known Risks or Let its AI Decide: Organizations can upload their specific list of key known risks directly into the platform in its existing format, or Signal's AI platform can determine and suggest high-priority risks based on an organization's profile. * AI-Powered Data Scanning: Risk Scanner processes these risks against Signal AI's extensive architecture of unstructured global data, spanning billions of data points across 226 regions and translated from 120+ languages, for automated tracking. * Dynamic Assessment: The platform instantly maps the findings into an automated risk assessment matrix, spanning across languages and regions, categorizing data and scoring risks to show exactly which threats are escalating and what needs to be prioritized. "Signal AI's AI-powered capability to transform millions of data points in real-time can now speak the language of risk owners using their existing, proprietary risk registers," says Tara Lynch, Product Director for Risk at Signal AI. "This is the kind of automation that will identify signals early, support with time saving, and make companies more resilient." Availability. The Risk Scanner capability is currently available for Signal AI partners and clients. Organizations looking to move from static risk register monitoring to an AI-powered, data-driven risk posture can request a demo at signal-ai.com/contact-Signal Media Ltd. Media Contact Margo Connolly

Signal AI appoints Thor Mitchell as Chief Product & Technology Officer. LONDON / NEW YORK - June 4, 2026 - Signal AI, a global leader in AI-driven reputation and risk intelligence, today announces the appointment of Thor Mitchell as Chief Product & Technology Officer (CPTO). Mitchell brings two decades of experience scaling products and technology at some of the world's most successful companies, including Miro, Crowdcube, and Google. It's Signal AI's belief that the AI platforms that win over the next five years will be those that combine the necessary human skill sets and talent with innovative technology. The appointment marks Signal AI's first major C-suite investment in product leadership following a $165 million funding round with Battery Ventures. It demonstrates where Signal AI is deploying its growth capital: into world-class human talent and infrastructure to build for an AI-native future. Leadership with a proven track record. Most recently, Mitchell served as VP of Product at Miro, where he helped lead the platform through extraordinary growth. He was instrumental in building Miro's developer platform and ecosystem, which now serves millions of users worldwide. Before Miro, he served as Chief Product Officer at Crowdcube, where he delivered a B2C mobile strategy that doubled user engagement and captured one-third of all investor activity within its first year. His earlier roles at Google, spanning California, London, and Sydney, saw him lead product teams across the Google Developer Platform and Google Maps. For the past year, Mitchell has served as an Executive-in-Residence at Balderton Capital, one of Europe's leading venture capital firms, where he advised founders on building and scaling world-class products in the AI era. In that role, he witnessed firsthand how the AI platforms winning in the market are those backed by exceptional cross-functional leadership, not just exceptional technology. "It's clear from my conversations with founders across Europe that AI is dramatically accelerating the pace of product development", Mitchell said. "AI can unlock a step change in business performance when combined with deep customer insight, strong commercial instincts, and radical creativity. Thanks to their world-class data, clear mission, and exceptional team, Signal AI is uniquely positioned to transform how enterprises navigate risk and reputation, and I am delighted to join them in realising this vision." A strategic investment in Product & Technology. Mitchell's appointment unifies product and technology at the leadership level, bringing a single strategic voice to the company's core mission: building a decision intelligence platform that helps leaders see clearly, decide confidently, and act boldly. At Signal AI, he will represent product and technology at the Board level and work alongside David Benigson to chart the company's product vision for the next five years. "Thor is exactly the leader we need at this moment," said David Benigson, CEO & founder of Signal AI. "His ability to scale products and teams and to think strategically about how technology and business align will be transformational. But what really convinced me to recruit Thor was his conviction that the best product teams are built around people, not hype. In a market crowded with AI claims, Signal AI's edge is our team. Thor is one of the leaders who will amplify it." Timing and onboarding. Mitchell begins in early June and has already started his onboarding process. His appointment follows recent product milestones, including the acquisition of Memo and its proprietary readership data, a strategic partnership with Dow Jones Factiva, and the launch of AI Citations, positioning Signal AI as the platform of choice for enterprise reputation and risk intelligence. About Signal AI Signal AI is a global leader in AI-driven reputation and risk insights. The company serves 800+ global customers across Fortune 500 companies, ingesting and transforming the world's data across 226 markets and 120+ languages to navigate industry trends, manage reputational shifts, and mitigate risks. Learn more at signal-ai.com. Media Contact: Margo Connolly

Signal AI launches AI Citations to help brands measure and influence presence in ai-generated answers. LONDON / NEW YORK - May 27, 2026 - Signal AI, the global leader in reputation and risk intelligence, today announced the general availability of AI Citations, a new capability within its readership data platform, formerly Memo, that reveals how brands appear in AI-generated answers and which earned media articles drive that visibility. With AI Citations, PR and communications teams can, for the first time, systematically track, benchmark, and influence their brand narrative across leading Large Language Models (LLMs), including ChatGPT, Gemini, and Perplexity. The way consumers find information is fundamentally shifting. Industry data shows that 80-90% of LLM responses rely on earned media, news articles, analyst coverage, and third-party publications, rather than a brand's owned content. Yet the current generation of GEO and AI search optimisation tools is built almost entirely around owned content: they advise brands to rewrite website copy, restructure blog posts, and adjust metadata in the hope of influencing LLM outputs. That approach addresses, at most, the 10-20% minority of what LLMs actually cite. The 80-90% earned media majority has remained invisible and unmeasured. AI Citations addresses this gap directly. The capability provides four core metrics: * Brand Visibility Score: the percentage of AI conversations in which a brand appears, which, paired with readership data, quantifies the downstream impact of earned media. * Focal Mentions: a count of total citations for a brand name and the number of articles cited, benchmarked against direct competitors. * Top Prompt Categories: a grouping of the narrative themes users most frequently ask LLMs about, surfacing the full prompts and AI responses that trigger brand citations. * Top Cited Publishers: a leaderboard of the domains LLMs treat as trusted sources for brand information, enabling teams to shape their earned media strategy toward the outlets AI models actually rely on. AI Citations is made possible by Signal AI's acquisition of Memo, combining industry-leading reputation intelligence with the world's only platform that provides direct readership data from publishers. Viewing AI Citations alongside real readership figures allows communications teams to see not only what the AI says about their brand, but why - tracing citations back to the specific articles and publishers that carry the most weight with LLMs and human readers alike. The launch comes as Generative Engine Optimisation (GEO) emerges as the new frontier of search strategy. Signal AI positions AI Citations as the essential measurement layer that makes GEO actionable: without knowing which publishers LLMs trust and which narratives drive visibility, any optimization effort is based on guesswork. AI Citations provides the scouting report; GEO becomes the game plan built on top of it. "The conversation in the market has been almost entirely about optimising owned content for LLMs and that matters, but it's only a fraction of the picture," said Karlie Santucci, Chief Customer Officer at Signal AI. "What we found with customers at both Memo and Signal AI is that the real question is: which earned media does the AI actually trust, and what is it saying about us? Without AI Citations and readership data, GEO is just guessing what to optimise. You need the measurement before the strategy can work." AI Citations is now generally available as part of the Signal AI readership data platform. About Signal AI Signal AI is a global leader in AI-driven reputation and risk insights. The company serves over Fortune 500 companies, ingesting and transforming the world's data across 226 markets and 120+ languages to navigate industry trends, manage reputational shifts, and mitigate risks. Learn more at signal-ai.com. Media Contact: Margo Connolly