Amsterdam-based real estate startup Epum has raised $1.6 million in pre-seed funding.
Epum was founded by two former commercial real estate developers (Royden Cooper and Spencer Stieff), a former Adyen senior software engineer (Leonardo Costa), a former Globality senior data scientist (Tomasz Pietruszka), and a world-leading researcher in the field of geospatial artificial intelligence, a PhD graduate from the Vienna University of Technology (Marvin Mc Cutchan).
Epum’s platform contains the largest real-time dataset of urban zoning and planning activity across the United States.
Based on this dataset and proprietary algorithms, the platform delivers a powerful commercial real estate development site selection solution, evaluating local demand drivers, zoning, owner profiles, demographics, competitive supply, land area, topography, transportation data and more to identify and support ideal acquisition opportunities.
Epum already has partnerships with two national commercial real estate developers and one real estate private equity fund.
“Raising $1.6 million in our pre-seed round marks a major milestone for Epum and we are excited to have additional resources to serve our clients,” said Royden Cooper, CEO of Epum.
“Commercial real estate developers are the main catalysts of value creation in the commercial real estate ecosystem as they are the architects of the future of cities.
“With rising interest rates creating uncertainty for the industry over the past 12 months, we’re pleased to support developers with new tools to help them de-risk their projects and increase assets under management.”
Curiosity VC led the oversubscribed round with co-investment from NP-Hard Ventures, Remote First Capital and HearNelt VC.
The investment will accelerate the development and distribution of Epum’s commercial real estate research platform, which is designed to enable developers, investment managers and lenders to identify optimal development sites based on inputted parameters, securely organize their proprietary data, forecast submarket trends using purpose-built machine learning models, and generate investment committee memos more than 10 times faster than traditional human analysts.
Main image: Epum. Photo: Uncredited.
