Reza Sardeha, Founder and CEO of Anyone.com – Interview Series

Reza Sardeha is a serial tech entrepreneur and innovator based in Amsterdam. Before launching Anyone.com, he served as CEO of Dan.com—where he helped reshape the domain-name market using blockchain and streamlined digital transactions—and also founded the award-winning web agency AZS Media Group. With a track record of building scalable, user-centric platforms, Sardeha is now focused on solving one of the world’s largest challenges: access to homeownership.

Anyone.com is a next-generation real estate platform that brings the entire home-buying and selling process into a single digital workspace. The platform enables buyers, sellers, agents, and related professionals to manage listings, viewings, offers, negotiations, and closures seamlessly and transparently. With AI-powered agent matching, end-to-end workflows, and plans for an “Anyone Mortgage,” the company aims to make property ownership faster, fairer, and more accessible globally.

What personal experience or insight led you to found Anyone.com, and how did your journey building and exiting Dan.com influence your decision to tackle real estate with AI as the core solution?

After building and exiting Dan.com to GoDaddy, I realized I didn’t want to solve small problems in relatively low impact industries. I wanted to fix something truly broken. Real estate stood out. It’s one of the last trillion-dollar industries still running on outdated, fragmented tools. At Dan, we built infrastructure that made domain transfers and ownership seamless. I saw the opportunity to do the same, but on a much bigger scale, with real estate, powered by AI. Why AI? Innovation in my opinion is nothing more than process optimization. AI is a supertool to accomplish that when utilized properly hence us going in this direction.

Home buying is often slow, expensive, and opaque. How exactly does AI at Anyone.com cut through that complexity to make ownership more accessible?

Our AI removes guesswork from every stage. From matching you to the right agent to helping you make smarter offers (coming soon) to managing every step digitally. It makes the process faster, cheaper, and far more transparent. We’ve automated the “what do I do next?” moments buyers always struggle with and we provide buyers with everything they need to succeed instead of just a part of it. Traditional portals only help with discovery of properties for example but the buyer journey is much more extensive than just that.

Your platform analyzes over 12 billion data points. Can you share a concrete example where the AI found an unexpected match or insight a human likely would have missed?

We once matched a buyer moving from London to Lisbon with an agent who had handled a near-identical cross-border transaction just months earlier, even though they weren’t in the top search results and had no idea which agents were good or not in Lisbon. A human wouldn’t have known that context. Our AI surfaces nuance that’s impossible to track manually and bases decisions on ALL data available instead of fractions.

Trust is a huge issue in both real estate and AI. How do you design algorithms that people will feel comfortable relying on for life’s biggest purchase?

We prioritize transparency. Users see why they’re matched, what criteria was used, and can always explore alternatives. AI doesn’t replace human judgment, it enhances it. Besides that, we use AI to match you but eventually an expert real estate agent assists you through the transaction on our platform.

Real estate markets vary wildly from Amsterdam to New York to Tokyo. How do you train AI models to adapt to such different local rules and behaviors?

We don’t try to force a global model onto local markets as we strongly believe real estate transactions need local expertise. Our AI model takes in all agents’ performance data from each and every local area and provides tailored recommendations based on that.

Beyond faster transactions, what new possibilities does AI unlock — are we heading toward a world where algorithms negotiate deals or structure financing themselves?

Absolutely. We’re already exploring AI-guided negotiation support and personalized financing structures. The endgame is a system that can optimize a deal in real-time, balancing price, timing, and financing to make homeownership far more accessible.

Under the hood, what kinds of machine learning models drive the platform, and how do you train them to balance speed, accuracy, and fairness in real estate decisions?

We use a mix of supervised learning, collaborative filtering, and natural language models. The matching engine, for example, balances agent performance, buyer preferences, and transaction context. We continuously retrain on real outcomes to reduce bias and increase precision. We started working on the solution over 2 years ago and launched just a couple of months ago so we need more time to get better at what we do as we gain access to more capital but the solution works already and fast. Our engineers handle massive amounts of data but solved all scalability issues we faced.

Your shared equity mortgage model sounds disruptive. How does AI determine affordability and tailor financing options to individual buyers?

We do not offer or provide the shared equity mortgage model on scale yet, but the first step we’re working on is to match you with mortgage advisors and providers in a similar way we match you with real estate agents, and the step after that is to provide the right tools to mortgage providers to optimise their workflow especially that of underwriting teams.

With billions of property records across 10+ countries, how do you ensure your AI isn’t just faster but also fair, unbiased, and accurate in its recommendations?

We test our models across demographic segments and markets regularly and later down the road will provide our AI the capability to improve its performance. We never allow agents or our AI to boost a specific recommendation and the model is always trained to provide the best recommendation and not a biased one so by design it is unbiased. On our end we then just need to make sure our data is accurate since the model is trained on data in the end and data integrity is key to safeguard on scale.

If AI fundamentally changes the role of the human real estate agent, what does that new role look like in a world shaped by Anyone.com?

Agents become trusted advisors again not admin workers. With AI handling the workflow and busywork, agents can focus on strategy, relationships, and closing deals. It’s about elevating their role, not replacing it.

Thank you for the great interview, readers who wish to learn more should visit Anyone.com.