Platforms · Software · Providers · Markets
Obsero has secured $1.2 million to build software that tracks how brands are surfaced by AI search services. SFC Capital headed the seed financing, joined by angel investors and several of the company's customers, whom it has not identified.
The London company was established in September 2025, putting the funding 13 months after its launch. Its founders, Michael Logue and Andy Francos, previously held marketing roles at IG Group and are applying that experience to the shift from conventional search towards generated responses.
Logue spent more than 13 years across two stints at IG and IG Group. His most recent position there was Product and Marketing Director for its international business; between those periods, he was VP of Growth at tastytrade.
Francos has worked in organic search for two decades, including roles at Cazoo, P&G and IG. He said Cazoo associated £252 million in revenue with organic search during his tenure.
Obsero sends simulated customer queries to Google AI Mode, Perplexity, Claude, Gemini and ChatGPT. It records whether a client's brand appears, its position, the answer's tone and the sites cited as sources. The founders say the company analysed more than 10 million AI-generated answers during its first year. It plans to turn learning from its consulting work into specialised AI agents for marketing teams.
As Finance Magnates reported, Zopa, Pepperstone and Zoopla are among Obsero's disclosed customers. The company says it also works with unnamed brokers and fintech startups. It plans to expand its commercial operations and grow its engineering team to more than twice its current size. In a J.D. Power survey, 51% of consumers said they had turned to AI for financial information or advice. Investing and stock-market topics were among the frequent subjects. The study does not establish that visibility in AI responses brings customers to brokers.
The integration question
For infrastructure and marketing operations, the open issue is how these measurements would fit into existing reporting. Which queries are covered, how frequently are they run, and can results be exported for comparison over time? The report gives no collection cadence, integration options, data-retention terms or pricing, so teams cannot yet estimate implementation or recurring costs from the information disclosed.
Before treating visibility as an acquisition metric, teams should ask how the service distinguishes changes in a model's answers from changes in brand presentation, and how it tracks cited sites and tone across providers. The reporting does not detail the methodology or show a link between a brand mention and customer acquisition. Those answers would help determine whether the tool belongs in marketing analytics or also needs review by data and platform teams.
A pilot would also need a clear basis for comparing results across ChatGPT, Gemini, Claude, Perplexity and Google AI Mode. Operators can ask whether the query set reflects the questions their customers use when researching financial products, and whether the results can be reproduced over time. Until those details are clear, the frequency and cost of monitoring remain open questions for any team considering a recurring budget.
