inAtlas: geospatial intelligence for real estate
Last Updated on 3 July 2025 by Urbanitae
In a sector as dependent on location as real estate, having accurate data and tools powered by geospatial intelligence makes all the difference. That’s why inAtlas was founded over a decade ago, with the mission of helping companies identify opportunities, assess risks, and plan with greater precision. We spoke with its CEO, Luis Falcón, about how the company has contributed to professionalizing territorial analysis and transforming decision-making in the Spanish real estate sector.
How did inAtlas get started, and how have you contributed to revolutionizing the way companies make strategic decisions?
inAtlas began its activity in 2010 with the goal of democratizing access to business intelligence tools and qualified data, highlighting the importance of the geospatial dimension in business. From the outset, we set out to change how organizations define their strategies—moving from intuition to data, with a geospatial perspective. Instead of relying solely on Excel or static reports, we offer a dynamic, visual, and territorial approach that enables our clients to see the potential of their business in every square meter of the country.
Our revolution has been making complex information accessible and operational. Today we work with major operators, manufacturers, export entities, franchises, real estate agencies, insurance companies, and utilities, integrating big data into their expansion processes, location assessment, risk analysis, or commercial prospecting. We also work with public administrations seeking to enhance their diagnostic capabilities to plan more effective urban policies.
How do you differ from other firms offering similar solutions?
inAtlas combines three key differentiators. First, it offers territorial granularity down to the building entrance, including cadastral information. Second, it maintains a B2B market database, updated daily, containing over 3.5 million active businesses in Spain and 600 million globally across 200 countries and territories. It also includes 400 million customs operations and more than 150 variables on consumer profiles worldwide (B2C market). Finally, it features powerful geospatial functionalities that allow for instant cross-analysis, segmentation, and simulations.
Additionally, we are a 100% SaaS (Software as a Service) company, with our own platform, no external technological dependencies, and a multidisciplinary team with both technical and business expertise. We work with data, yes—but also with the right questions: Where to invest? Where is there more risk? Where are my customers and those of my competitors?
How is big data transforming real estate?
Big data has enabled the real estate sector to move beyond generic approaches and toward hyperlocal decision-making. It’s no longer just about the location of an asset, but understanding everything behind each site: competition, demographics, income levels, consumption habits, mobility, or tourist pressure.
Today, a developer or fund can anticipate an asset’s potential performance, assess a project’s feasibility, or calculate a location’s commercial appeal using real and up-to-date information. This transformation is creating a more professional, transparent, and efficient sector.
It also helps address structural challenges. Cities face the task of balancing economic development with access to housing. This type of analysis enables more visionary planning, combining profitability with social cohesion—something essential if we want our cities to remain competitive and livable.
“Big data has enabled the real estate sector to move beyond generic approaches.”
In a market with so many information sources, how can we identify those that offer reliable data?
Reliability comes from traceability and consistency. We work with verified official sources—such as the Cadastre, INE, Business Directory, and CNIG (National Geographic Institute)—which we then process and validate using our own models. What matters is not just having data, but understanding what it means, how it’s combined, and what it’s used for.
Moreover, the ability to cross-reference different sources helps reduce errors and add depth. For example, a postal address may seem clear, but without precise georeferencing, it can lead to wrong decisions. We connect coordinates, income levels, property types, and economic activity to provide a reliable and actionable view.
You recently launched GeoBiz, a tool that represents a turning point in real estate analysis. What are its functionalities?
GeoBiz Real Estate is our most advanced SaaS solution for professional analysis. It allows users to visualize and compare locations based on socioeconomic, commercial, tourist, and housing indicators. Some of its key features include:
- Automatic location assessment (heatmaps, scoring, reports)
- Competitor analysis and commercial concentration
- Potential demand estimates and customer segmentation
- Integration with client-owned or third-party databases
- Export of results via reports or APIs
Its greatest strength is usability: with just a few clicks, you can make informed decisions without needing expertise in GIS (Geographic Information Systems) or statistics.
“Various developers use GeoBiz Real Estate to identify properties and analyze the local real estate market.”
Can you share a specific case where inAtlas tools made a significant impact?
A recent case involves a restaurant chain that used our tools to redirect its expansion strategy post-pandemic. We analyzed their current network, competitors, post-COVID mobility, and new high-potential areas. The result? Within a year, they opened 12 new locations with average revenues 30% higher than their previous ones.
Several developers use the sector-specific GeoBiz Real Estate tool both to identify properties and to analyze the real estate market around their assets. This helps them make accurate pricing decisions and find potential buyers.
Another example is an insurance company that optimized its network of agents and reduced claims in high-risk areas using our geolocated risk scoring. The key lies in combining data with industry knowledge and agile decision-making.
What challenges does a traditionally conservative sector like real estate face?
The main challenge is the real digitization of processes—not just as a display, but as part of the decision-making core. Many companies still resist changing work methods that were effective in the past but are no longer competitive today.
Another obstacle is data integration in collaborative environments: developers, investors, agencies, public administrations… Multiple types of information must be integrated and made to “speak” to each other. Lastly, there’s a training challenge: understanding what data is, how to interpret it, and how to turn it into value.
We’re also at a point where the private and public sectors must align more than ever. Planning affordable housing, attracting talent, or revitalizing neighborhoods cannot be done without accurate data and cross-sector collaboration. Transformation means understanding the market—but also the social and urban environment in which it operates.
What are your business expectations?
inAtlas is in a phase of consolidation and growth. We’ve strengthened our positioning in nine sectors: real estate, retail, finance, import-export, tourism, insurance, industry, energy, and telecommunications. Additionally, we are expanding strategic alliances both in Spain and internationally.
But beyond growth, our ambition is clear: to become the benchmark in business intelligence based on territorial logic, applied to decision-making. We want to help companies be more successful and cost-efficient, and help institutions plan better, reduce risks, and ultimately create smarter and more sustainable environments.
