redalpine’s Post

A compelling example of how AI is moving beyond generation toward real-time understanding. 🔍🤖 The partnership between Albatross AI and Wallapop shows what adaptive, perception-driven AI can unlock in complex, high-velocity marketplaces, with engagement and intent metrics that speak for themselves. Strong validation of the vision backed by redalpine, and congrats to Kevin Kahn, Matteo Ruffini, Johan Boissard, as well as Dr. Oliver Pabst and Marc Moesser, for pushing discovery into a new, more contextual era. A milestone worth watching closely. #AIInnovation #Marketplaces #AppliedAI

Albatross AI just rolled out in-session AI discovery across Wallapop, one of Europe’s leading C2C marketplaces and the results speak for themselves: 📈 +118.9% increase in user engagement ❤️ +104.8% increase in interactions & favorites 🛒 +46.9% increase in purchase intentions …all while surfacing previously unseen listings to real buyers.  This is discovery that understands what users want right now, not what they did yesterday. If your catalogue is large, dynamic, or hard to organize you’ll want to see how this approach could unlock value for your business. 👇 Let’s talk about real-time discovery + smarter relevance. #AI #ecommerce #marketplaces #personlization #productdiscovery #AIdriven

AI Discovery Domination - E-Commerce Edition | PART VII | "If a customer asked AI what to buy in your category right now… would your brand be mentioned?" Not theoretically. Not someday. Right now! That question matters more than most founders realize. Because AI doesn’t announce when you’re being ignored. It simply recommends someone else. Over the past week, we’ve broken down how AI discovery works, why marketplaces create dependency, how recommendation mechanics function, and what framework serious brands use to prepare. Now it’s simple. Are you visible inside AI conversations or not? At XED AI SOLUTIONS, we built an AI Visibility Audit specifically for e-commerce brands that want clarity, not assumptions. We assess: • Whether your brand is machine-understandable • Whether your authority signals are strong enough • Whether competitors are gaining AI ground • Whether you’re recommendation-ready No fluff. No vague reports. Just a clear picture of where you stand. If you want to know the truth about your AI visibility, reach out. It’s better to know now than six months from now.

AI systems are already influencing buying decisions. The real question is Are you part of those recommendations? At XED AI SOLUTIONS, we’ve launched a dedicated AI Visibility Audit for E-Commerce Brands designed to answer one critical question. Are you recommendation-ready? This is not a generic SEO audit. This is an AI recommendation readiness assessment. If AI is influencing purchase decisions in your category, invisibility is costing you revenue. If you’re serious about being recommended, not just ranked. Book your AI Visibility Audit with XED AI SOLUTIONS. Let’s see where you stand.

Your AI Agents sucks but it wont tell you that. The consumers will. They will take their business somewhere else. Are you ready for it?? The checkout button is about to become obsolete. Agentic commerce — where AI agents don't just advise consumers but act on their behalf — is no longer a concept. It's being built right now by Infosys, OpenAI, ACI Worldwide, and others racing to define the protocol stack that governs how AI buys things. The question isn't whether your brand will sell to AI agents. It's whether you'll even know when it happens. Most retail and e-commerce teams are still optimizing for human attention spans. That's the wrong game. The brands that win the next decade will be the ones building agent-aware digital ecosystems today — where every product signal, pricing rule, and transaction flow is designed for machine-speed decision-making. Are you building for the customer, or the customer's AI?

AI is obviously everywhere, but after (already!) years of hype and buzzwords, you have to eventually do the deep dive and show what actually have been done ✅ and shipped 🚀. Together with David Roberts, Matthias Frechen, Kamil Konikiewicz & Ireneusz Gawlik we represented Allegro on CMPO Forum organised by Permira to do exactly that. And honestly I'm proud that when we were asked "how many AI implementations are really live out there" - our responds was dozens+. Together with Kamil we presented example use cases - both how Agentic AI acts a powerful accelerator of personalization and marketing workflow optimization or how we enhance Customer Journey experience (and increase CVR), specifically on Product Pages with Ratings & Reviews. 🤔 Interesting take for you maybe this ➡️ implementing AI doesn't necessarily mean things will sky rocket "just like that". Tbh, the first implementation of "AIing" product ratings and reviews (to eliminate friction of countless records by extracting key takeaways for consumers) failed 🛑 even worsening the experience. But in Allegro failed experiment means gained learnings 📚 so we can iterate. And so we did, team led by Joanna Mokijewska 👏 delivered an upgrade that boosted all the sexy metrics you want to see green. And you can test the current performing solution by checking ratings & reviews on our Product Page. 👨🏫 So: 1. Don't expect implementing LLMs and stating "AI-powered" will do all the magic 2. If implemented without proper learning curve it can even decrease your metrics. But the potential may be still there. 3. Always start small and simple so you can validate which part of solution works well and which one should be iterated or canceled. Is it obvious? You could say that, but I've learned that from time to time even obvious things should be read to refresh your top of mind perspective. Huge thanks to Lisa Zhang for organising this event and giving us the opportunity to show what Allegro is cookin to contribute in transforming e-commerce as we know it. I'm hyped for all the future in front of us and happy for being where I am right now ☺️

AI won't replace e-commerce sellers. But sellers using AI will replace those who don't. I talk to sellers every week. The ones growing fastest aren't the ones with bigger teams. They're the ones who automated the boring stuff. Listing optimization. Translation. Compliance checks. Product data imports. Reporting. None of this requires human creativity. All of it requires consistency, speed, and accuracy — exactly what AI is built for. The sellers still doing this manually are spending 30-40 hours a week on operations. Their competitors spend 4. Same catalog size. Same marketplaces. Different approach. The gap is only getting wider. Here's what I've learned building AI tools for e-commerce: → The bottleneck is never the AI — it's the decision to use it → Sellers don't need "more features" — they need fewer tasks → The best automation is invisible — it just works while you focus on growth → ROI shows up in the first week, not the first quarter You don't need a bigger team. You need better systems. #AI #Ecommerce #Automation #AmazonSeller #FutureOfWork

For years, conversations about AI and commerce felt frustratingly abstract. Optimize for agents. Be ready for the future. Prepare for ambient commerce. None of that was actionable. It was atmosphere, not instruction. Google’s Universal Commerce Protocol is refreshingly concrete by comparison. It defines how inventory is checked, how pricing is verified, how checkout is triggered, and how errors are communicated.  This clarity will allow teams to stop speculating about what readiness means and start auditing their systems against specific criteria. For a mid-size retailer, this might simply mean discovering that their inventory updates lag by two to four hours.  That is not an AI problem. It is not even a new problem. It is a solvable operational problem that has been tolerable in traditional ecommerce but becomes a barrier in AI commerce. The shift from "Should we be thinking about AI?" to "Here are the twelve fields in our feed that need work" is profound.  It converts anxiety into a project plan, and that is what unlocks action for most organizations. 

We’re excited to see Albatross AI announce a strategic partnership with Wallapop, bringing adaptive, in-session AI discovery to one of Europe’s leading C2C marketplaces 🙌 Wallapop becomes one of the first consumer-to-consumer platforms globally to move beyond static, history-based recommendations toward real-time perception - technology that understands user intent as it unfolds. What does that mean in practice? If a user starts browsing a second-hand sofa and then shifts to rugs and floor lamps, discovery adapts instantly - understanding the move from evaluating one item to furnishing a space. Instead of showing more sofas, the system surfaces complementary, style-matched listings across categories, including items the user didn’t explicitly search for. 🛋️ 🪑 🖼️ This is the shift from AI that predicts based on the past… to AI that understands the present. The numbers in early production have been outstanding: • +118.9% increase in user engagement • +104.8% increase in favourites & interactions • +46.9% increase in purchase intentions Read more on the partnership via Forbes: https://lnkd.in/eXey3s5S We backed the Albatross team because we believe personalisation has seen surprisingly little true innovation over the last decade. Generative AI transformed content creation. Real-time perception is transforming how content is discovered. This partnership with Wallapop is one of the earliest large-scale commercial deployments of adaptive AI discovery in recommerce - and a powerful validation of that vision. If you’re interested in why we backed Kevin Kahn and the Albatross team, and why we believe discovery is the next frontier of AI, read more here: 🔗 https://lnkd.in/eiGM_yqX 🔗https://lnkd.in/ejaxxNuX #AI #AIdiscovery #FutureofRetail

A new form of ecommerce is emerging. ***Visual commerce is approaching structural phase transition.*** Visual commerce is the ability to buy a product directly from what you see in a video, image, or live stream — by simply clicking on it. No search. No leaving the content. This is morphogenesis, not incremental improvement. The dominant sequence — see → exit → search → find → buy — is structurally unstable. A new attractor is emerging: see → click → buy Lower friction. Lower resistance. Higher conversion. Hysteresis is high. Once adopted, the system does not revert. This transition is part of a larger fractal restructuring of commerce driven by AI, alongside adjacent transitions such as conversational AI purchasing and AI-powered virtual product trials. (February 25, 2026) Structural Analysis follows (next post.)