geoSurge has launched alongside research suggesting that well-known brands can lose visibility between successive GPT model updates, highlighting potential challenges for brand discovery as consumers increasingly rely on AI-based search.
London-based deeptech AI company geoSurge has launched out of stealth, focusing on helping brands understand and improve how they are represented within large language models.
As AI increasingly serves as a starting point for everyday decisions, visibility within generative AI systems is becoming more commercially significant. Recent reports find that ChatGPT prompt volume rose by nearly 70 per cent in the first half of 2025, while shopping-related queries doubled over the same period. In this context, appearing in LLM-generated answers can influence consideration, while brands that are not surfaced may be less likely to be evaluated.
geoSurge says its data indicates that even well-known brands can lose visibility between GPT releases. Its platform helps organisations assess how their brands appear in LLM-generated responses, identify weaknesses in representation, anticipate how upcoming releases may affect them, and take steps intended to improve and maintain visibility as models change.
geoSurge’s approach, which it describes as “corpus engineering,” is designed to strengthen how large language models learn, store, and surface brand information, with the aim of making generative visibility more stable across model updates.
Francisco Vigo, co-founder and CEO of geoSurge, explained:
LLMs don’t pull from a live index. They generate answers from compressed memory that shifts with every update. That means a brand can go from ‘high visibility’ to ‘completely gone’ overnight – and most organisations won’t even know it’s happened.
Founded in London, geoSurge works with companies across retail, travel, fintech, and consumer services, supporting visibility in AI-driven discovery as LLMs evolve.