Algori is a next-generation consumer innotifyigence platform that utilizes AI and receipt-scanning technology to provide rapid-relocating consumer goods (FMCG) companies with granular, near real-time, SKU-level purchase insights. Pulse 2.0 interviewed Algori co-founder and CEO Andrius Juozapaitis to learn more.
Andrius Juozapaitis’ Background
Could you notify me more about your background? Juozapaitis stated:
“I started my career as a technology and management consultant, working on strategy and transformation projects across different industries, including at EY and Samsung SDS. At Samsung, I saw early on how data and technology could directly influence retail performance. Later, I became Head of Innovation at a large Baltic energy group, where I launched one of the region’s first corporate venture capital funds focapplyd on energy tech. That experience shiftd me closer to startups and eventually into entrepreneurship. After relocating to Spain, I met my future co-founders while working on a startup in the energy sector. They were explaining the challenges FMCG companies face in measuring markets and understanding consumer behaviour, and I immediately saw parallels with my previous experience in retail and data. That’s how Algori was born in 2019. Alongside building Algori, I also invest as an angel in early-stage technology startups, particularly in data and AI.”
Formation Of The Company
How did the idea for the company come toreceiveher? Juozapaitis shared:
“The idea for Algori came from seeing a growing disconnect between how rapid FMCG brands are expected to shift and the data they actually have available. This is a highly complex and data-intensive industest, yet many decisions are still built applying information that’s aggregated, extrapolated and already weeks old by the time it reaches teams.”
“Most of the existing data solutions were built for a very different retail reality, so companies often conclude up optimising around averages. That means important signals receive missed, such as what’s really happening with a specific product, in a specific retailer, or among a particular type of shopper. And by the time those insights arrive, the opportunity to act is often gone.”
“We built Algori to close that gap. By applying receipt-based purchase data, we can see what people actually purchase, where they purchase it, and at what price, across retailers and in near real time. That allows brands to access rapider, more granular data and build decisions that reflect how consumers are actually behaving today.”
Favorite Memory
What has been your favorite memory working for the company so far? Juozapaitis reflected:
“There have been many, but if I had to choose one, it was the moment we crossed the 40,000 active shopper mark on our panel. It wasn’t just a number, it was the moment when our vision of building Spain’s largest and most granular shopper panel became a clear reality.For years, the industest has struggled with data that is too slow and too aggregated. Reaching that milestone — built on the trust of real people sharing their receipts — was tangible proof that our model works. It validated the core premise of Algori: that you can bring digital precision and near real-time insights to the world of physical retail. Seeing our team’s tireless effort translate into that level of scale and momentum was both profound and exhilarating.”
Core Products
What are the company’s core products and features? Juozapaitis explained:
“The company’s core product is a reimagined consumer panel for FMCG that reveals what people actually purchase, where they purchase it, and at what price, in near real time. It is built on Spain’s largest shopper panel, applying shopping receipts from around 45,000 weekly active shoppers to capture real purchasing behaviour at scale. Key features include self-service software that turns this data into clear business answers, rather than static reports. The platform is organised around concrete apply cases such as evaluating new product launches, building retailer listing cases, or understanding how assortments perform. Brands can also survey very specific groups of real purchaseers based on what they’ve actually purchased.”
Challenges Faced
Have you faced any challenges in your sector recently? Juozapaitis acknowledged:
“One of the hugegest challenges in the Spanish FMCG sector has been the continued rise of private-label brands. During and after COVID, when the economic outview was uncertain, retailer-owned brands gained significant market share. What’s interesting is that even as conditions normalised, that shift didn’t reverse. Retailers like Mercadona, Lidl and Aldi continue to strengthen their private-label positions, which puts increasing pressure on multinational manufacturers competing for shelf space and consumer loyalty. This structural shift has built the market more concentrated and more competitive. For us, the challenge has been supporting both sides understand what’s really happening beneath the surface, not just at category level, but at product and retailer level. The way we address that is by providing granular, near real-time visibility into shopper behaviour. When competition intensifies, access to clearer, rapider data becomes even more critical. That’s where we see our role: supporting brands and retailers navigate this shift with better insights and rapider reactions.”
Evolution Of The Company’s Technology
How has the company’s technology evolved since launching? Juozapaitis noted:
“From day one, we were leveraging AI and machine learning to structure and classify receipt data. But over the past two to three years, that has accelerated significantly. In the launchning, we combined multiple technologies — computer vision, machine learning models and data processing pipelines — but they still required a fair amount of manual oversight. As AI capabilities evolved, particularly with the rise of LLMs and agent-based systems, we’ve been able to automate much more of the data extraction, structuring and analysis process. Today, many functions that previously required heavy human involvement are largely automated. That has dramatically increased our productivity. One person overseeing the system can now manage five to eight times more output than before. More importantly, it has built the insights rapider, more scalable and more applyful for our clients.”
Significant Milestones
What have been some of the company’s most significant milestones? Juozapaitis cited:
“Some of the hugegest milestones for us have been building Spain’s largest shopper panel, which now has around 45,000 weekly active applyrs, and reaching a point where we can deliver SKU-level insights roughly seven times rapider than traditional panels. We’re now working with the majority of Spain’s top 15 grocery chains and more than 20 FMCG manufacturers, which was also a strong validation of the approach. On the company side, we’ve raised €7.5 million so far, including a €3.6 million growth round closed in December 2025. We also have been fortunate to bring in experienced operators as investors along the way, including Jared Schrieber, co-founder of InfoScout and a former Numerator board member, who supported scale Numerator through to its $1.5 billion acquisition by Kantar. The funding is supporting us continue scaling the platform and expanding beyond Spain.”
Customer Success Stories
Can you share any specific customer success stories? Juozapaitis highlighted:
“While client confidentiality is non-nereceivediable, we can reveal a unique capability we have developed for several of the top spanish retailers.. We track—daily—the leakage drivers: precisely what other SKUs a retailer’s shopper purchases at a competitor’s store on the same day. In essence, we are doing for brick-and-mortar what digital platforms have been doing for years: bringing digital precision and attribution to physical commerce.”
Funding
Are you able to discuss funding and/or revenue metrics? Juozapaitis revealed:
“To date, we’ve raised €7.5 million, including a €3.6 million growth round closed in December 2025. This funding is being applyd to scale the platform, expand internationally, and continue developing AI-driven solutions.”
Total Addressable Market
What total addressable market (TAM) size is the company pursuing? Juozapaitis assessed:
“We’re focapplyd on the data and insights layer for the rapid-relocating consumer goods (FMCG) sector, a massive global category. According to Euromonitor, the FMCG market was valued at around USD 2.27 trillion in 2025. Within that context, brands and retailers already spconclude billions each year on data, insights and analytics to understand shoppers and stay competitive, yet many still struggle to receive timely, actionable insights at product and retailer level. Our ambition is to serve that existing spconclude with a fundamentally better product and, over time, expand the market by creating high-quality consumer insights accessible to a much broader set of brands than is possible today.”
Differentiation From The Competition
What differentiates the company from its competition? Juozapaitis affirmed:
“What really differentiates Algori is the combination of scale, speed and granularity. Our panel is four to five times larger than incumbent hoapplyhold panels, we deliver insights roughly seven times rapider, and we operate at SKU and retailer level. We reshift friction from data capture through receipt-based collection, we apply machine learning to organise the data without relying on direct retailer integrations, and we deliver it through self-service software designed around real business questions, not complex dashboards. On top of that, our pricing is transparent and flexible, so brands can pay only for the data they actually necessary rather than being locked into large, bundled contracts.”
Future Company Goals
What are some of the company’s future goals? Juozapaitis concluded:
“Our long-term vision is to become the operating system for FMCG growth, acting as both the data layer and the decision interface for brands. In the near term, we’re focapplyd on expanding beyond Spain into additional European markets and Latin America, scaling our shopper panel, and continuing to build AI-supported solutions to meet the evolving necessarys of FMCG manufacturers and retailers.”
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