Co-founder of One Place. Writes about how the product gets built, what the team is shipping, and how AI is changing the way people search for a home in Europe.
38 articles
One Place has been awarded R&D funding by Enterprise Estonia to develop AI models that combine computer vision and graph neural networks for scalable real estate valuation across Europe.
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Why no European company ever built a copy of Zillow, which half of the wish list is genuinely solvable here, which half depends on data most governments do not publish, and what the closest thing actually is in 2026.
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One Place enriches listings with straight-line distances to nearby places, from primary schools to major roads. Here is where those numbers come from, which ones can constrain a search today, and where the data is still not good enough.
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A general chat model will happily hand you a list of European properties, and some of them will not exist. Here is why that happens, what these models are genuinely excellent at during a property search, and the combination that actually works.
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Most buyers pick a country first and rationalise afterwards. A better order: decide what you are optimising for, compare the costs that never appear in a listing, ask how you would get out, and only then look at what your budget actually buys in each market.
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You can buy almost anywhere in Europe as an American, and that is the easy part. The financing, the closing costs, the tax that follows you home, the shape of the transaction and the absence of anything resembling an MLS are where the surprises live.
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Portugal is still open to foreign buyers and still one of the more straightforward purchases in Europe, but almost everything people believe about it dates from 2019. The process step by step, the real cost on top of the price, and the five things that catch foreign buyers.
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A practical 2026 guide to AI-assisted house hunting in France: where French listings actually live, which tools genuinely use AI, a workflow that combines them, and the parts of a French purchase no algorithm should handle.
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Why buyers go looking for a Properstar alternative, what to demand from a replacement, and an honest comparison of the options for European property search, from One Place to Idealista, Kyero, Green-Acres, and Tranio.
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AI search raises a fair worry: did it actually understand what I asked, and what did it silently leave out? How One Place makes its AI inspectable, tests it against real searches, and why nobody can pay to influence what you see.
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Listing photos carry more truth than listing text. Here is how One Place's computer vision reads every photo: sorting floor plans from photographs, recognising rooms, spotting CGI renders, and choosing the image you see first.
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Aggregators have a reputation for stale adverts and the same home shown five times. Here is how One Place recognises duplicates across portals, retires sold homes, and keeps prices honest, with the original sources always one click away.
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The biggest fear about using any property aggregator is the silent gap: the perfect home that never showed up. Here is how One Place builds its European coverage, how we measure it against local portals, and what we do when a listing is missing.
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Every listing on One Place is read by AI that turns free-form property adverts in any European language into one clean, comparable structure. Here is how that works, and why it is the foundation every filter stands on.
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A look inside the technology that lets One Place return accurate property results in seconds, from pre-computed vector indexes and distributed infrastructure to computer vision on listing images.
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