GeoPhy
The independent global source for property information and analysis for everyone with financial exposure to real estate.
| Date | Investors | Amount | Round |
|---|---|---|---|
| - | investor investor | €0.0 | round |
| investor | €0.0 | round | |
| investor investor investor | €0.0 | round | |
* | $85.0m Valuation: $85.0m 20.7x EV/Revenue -11.7x EV/EBITDA | Acquisition | |
| Total Funding | 000k | ||
| EUR | 2019 | 2020 | 2021 |
|---|---|---|---|
| Revenues | 0000 | 0000 | 0000 |
| % growth | - | 30 % | (23 %) |
| EBITDA | 0000 | 0000 | 0000 |
| % EBITDA margin | (150 %) | (157 %) | (177 %) |
| Profit | 0000 | 0000 | 0000 |
| % profit margin | (203 %) | (259 %) | (291 %) |
| EV | 0000 | 0000 | 0000 |
| EV / revenue | 00.0x | 00.0x | 00.0x |
| EV / EBITDA | 00.0x | 00.0x | 00.0x |
| R&D budget | 0000 | 0000 | 0000 |
| R&D % of revenue | 74 % | - | - |
Source: Company filings or news article
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GeoPhy, founded in 2014 by Teun van den Dries, has established itself as a notable player in the commercial real estate (CRE) technology space. Van den Dries, with a background in real estate and a Ph.D. in geosciences, envisioned a more data-driven approach to property valuation, which formed the bedrock of the company's mission. The firm aims to enhance transparency and efficiency in the CRE market by leveraging vast datasets and sophisticated analytical models.
The company's core business revolves around providing data-driven valuations and analytics for commercial real estate assets, with a particular focus on the multifamily sector in the United States. GeoPhy serves a clientele that includes institutional investors, lenders, and asset managers who require precise and timely information for their investment decisions. Its business model is centered on providing subscription-based access to its platform and data solutions, enabling clients to perform due diligence remotely and with greater speed.
At the heart of GeoPhy's offering is a platform that synthesizes traditional data sources, such as public records, with alternative datasets. This information is then processed using machine learning algorithms to produce automated valuation models (AVMs) and risk assessments. The platform delivers hyperlocal data, market benchmarks, estimated property values, and comparable sales, allowing users to assess the attractiveness and potential risks of CRE properties. This focus on objective, data-centric analysis helps clients to identify market opportunities and manage their portfolios more effectively. A significant milestone in the company's journey was its acquisition by Walker & Dunlop in February 2022, a move that integrated GeoPhy's analytical capabilities into a larger commercial real estate finance ecosystem.
Keywords: commercial real estate, data analytics, property valuation, machine learning, real estate technology, automated valuation model, multifamily properties, investment analysis, due diligence, proptech