geoSurge is an AI visibility and data science company that helps organizations understand and improve how their brands are represented across artificial intelligence platforms, including ChatGPT, Gemini, and Claude. Its technology combines AI visibility monitoring with a proprietary methodology called Corpus Engineering, which focuses on how AI models learn, understand, and represent brands over time. The company emerged from stealth in December 2025 and has expanded its customer base across four continents, serving industries including financial services, education, and hospitality. Led by Co-Founder and CEO Francisco Vigo, geoSurge is positioning itself around the growing importance of AI-generated answers in brand discovery and purchasing decisions. Pulse 2.0 interviewed geoSurge Co-Founder and CEO Francisco Vigo to learn more about the company’s origins, Corpus Engineering technology, approach to AI visibility, recent growth, and long-term plans for the emerging AI representation market.
Francisco Vigo’s Background
When asked about his background, Vigo shared:
I’m a data scientist by training. I grew up in Argentina, and I trained as a pilot for a while before ending up in data. I’ve always been drawn to disciplines that pair precision with creativity, and I look at markets the same way: through how systems learn and behave, not just how they appear on the surface.
That perspective is really the origin of geoSurge. I co-founded the company just over a year ago because I could see a structural change coming. AI systems, rather than search engines, were starting to decide how companies get discovered, understood and chosen, and almost no one was approaching that as a data problem.
How The Idea For geoSurge Came Together
When asked how the idea for geoSurge originated, Vigo explained:
It crystallized at the end of 2023. Watching these models improve, I became convinced AI was about to change how people find and choose companies, and that most of the market was about to misread it.
When my co-founder and I first sat down together, we built the earliest version of geoSurge in a single-day hackathon and framed the pitch around a deliberately provocative line: SEO for LLMs.
The real thesis underneath was subtler. How a brand shows up in an AI system isn’t just what the model retrieves in the moment; it’s what it has already learned and how it represents that brand over time.
As models know more, they search less, so the durable opportunity is the representation layer, not the surface.
The market moved fast on it: when we raised our pre-seed, the deck spread quickly and we had three term sheets within about three weeks. That early conviction from investors is what let us build the company properly around the thesis.
Favorite Memory Working At geoSurge
When asked about his favorite memory working at the company, Vigo recalled:
The stretch when the first pre-seed deck took off. I could watch it spreading across DocSend in real time, and suddenly people were jumping on calls with us on a Saturday.
I was pitching operators, angels, and founders I’d read about for years, sleeping about three hours a night and going for a run at 4 a.m. just to burn off the adrenaline.
When the first term sheet actually landed, one of them from an early investor in Monzo, it was surreal.
My whole life I’d had this feeling that my brain was running ahead of my circumstances, and in that moment it felt like things were finally course-correcting. That’s the memory I keep coming back to.
Core Products And Features
When asked about geoSurge’s core products and features, Vigo explained:
geoSurge combines two things. The first is visibility monitoring, which is now free. Any organization can download the geoSurge app, connect a ChatGPT, Claude or Gemini subscription it already has: and within a couple of minutes see how it’s represented across those models, including how answers differ between free-tier and paid-tier users.
The second, and the part that really differentiates us, is a proprietary methodology we call Corpus Engineering: a discipline designed to improve how a brand is understood and accurately represented by those models over time.
Our framework deliberately spans both sides of the problem: what AI systems retrieve in real time and what they already understand internally, because we believe AI visibility increasingly depends on both.
Challenges In The AI Visibility Market
When asked about the challenges geoSurge has faced in its sector and how the company has addressed them, Vigo explained:
The biggest challenge is that we’re competing against the market’s default assumption. Most of the category is focused on the visible surface of AI systems, prompt-level tracking and citation analytics, and we believe that’s a race to the bottom that will commoditize as the infrastructure matures.
Educating the market that the deeper opportunity is the representation layer takes conviction, which is also why we have tracking away for free. We have just launched the geoSurge desktop app, which lets any company track how it appears across the likes of ChatGPT and Claude for free, using an AI subscription the user already pays for. If surface-level tracking is going to commoditise anyway, we’d rather speed that up ourselves and compete where the hard problem is: what the models actually learn.
We’ve met it head-on by being technically credible: 80% of our team specializes in AI and data science, so we can demonstrate the approach rather than just assert it.
The category is also dominated by well-funded US firms. We’ve leaned into being the technical European challenger rather than trying to copy them.
How geoSurge’s Technology Has Evolved
When asked how the company’s technology has evolved since launching, Vigo explained:
We only emerged from stealth in December 2025, so it’s been a fast year.
The early work centered on visibility monitoring, giving organizations a reliable read on how they appear inside AI systems.
Since then the center of gravity has moved toward Corpus Engineering and the representation layer: not just measuring what models say about a brand, but understanding and impacting what they learn and remember.
In parallel we’ve doubled headcount and invested heavily in the data science and infrastructure needed to work at that depth.
Significant Company Milestones
When asked about geoSurge’s most significant milestones, Vigo highlighted its launch, international expansion, and fundraising progress:
A few stand out from a compressed timeline. Emerging from stealth in December 2025. Doubling headcount in the months since. Growing to customers across four continents and multiple industries, including Financial Services, Education and Hospitality.
In July closing an oversubscribed $12 million seed round led by AlbionVC, with Octopus Ventures, Play Ventures, Celero Ventures, Boost Capital and existing investors Passion Capital and Tuesday Capital, plus angels from Google DeepMind, Microsoft AI and Signal AI, one of the largest seed rounds in the AI-visibility category to date.
And most recently, launching the geoSurge app putting free AI visibility tracking in the hands of any company.
Funding And Revenue Metrics
When asked about the company’s funding and revenue metrics, Vigo shared:
On funding, yes. We’ve just closed an oversubscribed $12 million seed round led by AlbionVC, with participation from Octopus Ventures, Play Ventures, Celero Ventures, Boost Capital, existing investors Passion Capital and Tuesday Capital, and angel investors from Google DeepMind, Microsoft AI and Signal AI.
On the business itself, we’re keeping specific revenue figures private at this stage, but I can share the direction of travel: we’re just over 14 months old, we’ve doubled headcount since leaving stealth, and we already work with customers across four continents and multiple industries.
Demand from enterprise organizations is what’s driving the raise.
Total Addressable Market
When asked about the total addressable market geoSurge is pursuing, Vigo explained:
Rather than put a single number on it, the way I’d frame it is this: every major platform shift creates a new visibility economy.
Search created SEO. Social created the creator economy. AI is creating an entirely new representation layer that sits between companies and their customers.
As AI-generated answers increasingly shape discovery and purchasing decisions, we believe managing how a brand is represented inside these systems becomes a core strategic function, which puts our market on the scale of the categories that grew up around each previous platform shift.
What Differentiates geoSurge From Its Competition
When asked what distinguishes geoSurge from other companies operating in the AI visibility market, Vigo identified two factors:
Two things. First, our thesis: most providers optimize the surface, citations and retrieval, whereas we work on the underlying representation layer that increasingly drives AI outputs.
Corpus Engineering is our proprietary discipline for doing that, and it’s not something the surface-level tools are built to address.
Second, our technical depth: we’re a genuinely technical deep-tech company, not a wrapper, with 80% of the team in AI and data science.
We’re also the UK challenger leading at seed in a category otherwise dominated by US-headquartered firms.
Future Company Goals
When asked about geoSurge’s future goals, Vigo outlined plans to expand its technical capabilities and establish a broader market around AI representation:
The funding goes toward expanding our global research and engineering teams, investing in AI infrastructure and compute capacity, and accelerating the development of Corpus Engineering and our broader AI-visibility capabilities as enterprise demand grows.
The bigger goal is to establish the representation layer as a category, to be the company that defines how brands are understood by AI systems, the way SEO defined how they were found by search engines.
The Future Of AI-Driven Brand Discovery
When asked whether there were any additional topics he wanted to discuss, Vigo emphasized the potential impact of AI on how consumers discover businesses and how the internet generates revenue:
Only that I think we’re at the very beginning of this. The entire internet monetization model will need to be rethought.
What does an impression mean when an AI agent is making decisions on behalf of a user? What happens when customers no longer browse ten websites before making a purchase?
These aren’t abstract questions. They’re the start of what I’d call the fourth industrial revolution, and the representation layer is where a lot of it gets decided.
