Epum
Epum provides a real estate data science platform, SponsorAtlas, that utilizes machine learning models to forecast submarket trends and identify optimal development sites based on user-defined parameters. By offering bespoke datasets and dedicated data scientist support, Epum enables commercial real estate developers to streamline their acquisition processes and prepare investment memos over ten times faster than traditional methods.
- Artificial Intelligence
- Data & Analytics
- Enterprise Software
- Financial Technology
- Software Only
Funding
Raised to date
$1.6MRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Commercial real estate developers face challenges in identifying optimal development sites and forecasting submarket trends due to fragmented data and time-consuming manual analysis. Traditional methods of preparing investment memos are slow and often lack comprehensive, up-to-date data.
Solution
Epum provides a real estate data science platform that streamlines the acquisition process for commercial real estate developers. The platform, SponsorAtlas, utilizes machine learning models to forecast urban growth and identify promising development sites based on user-defined parameters. By aggregating and analyzing parcel-level data on commercial real estate project approvals, rezonings, and special exceptions, Epum enables users to visualize urban growth trends and uncover submarket-level insights. The platform offers features such as project tracking with email notifications, data visualization on a property level, and analytical tools for selected groupings of parcels or regions.
Target Audience
Epum's primary customers are commercial real estate developers seeking to streamline their acquisition processes, identify new opportunities, and gain insights into urban growth trends.
Features
- AI-powered software to screen, source, and support commercial real estate deals.
- Machine learning models to forecast population and urban growth.
- Aggregation of entitlement application data from government websites.
- Parcel-level data tracking of site plan approvals, rezonings, and special exceptions.
- Email notifications for new project approvals or status changes within specified areas.
- Visualization tools to analyze entitlement application data and urban growth trends.
- Analytical tools for selected groupings of parcels, submarkets, or regions.