Zero Energy Solutions
Active

An Indoor Climate Intelligence platform for commercial real estate

Climate Sensor Smart Home
Deep Learning

Business Overview

DESCRIPTION

Zero Energy Solutions has developed the first self-learning Climate Intelligence Platform for commercial buildings.

A Climate Node Network of sensors and controllers connects to all heating and cooling end-units and monitors relevant parameters, such as temperature, humidity, occupancy, and openings in every room. Applying data models and deep learning algorithms, the  system considers outside weather and utility tariffs to dictate the optimal route of action for every controlled zone, thus cutting up to 20% of energy costs without compromising on the end user’s comfort.

We set out to make Climate Intelligence a staple of smart buildings, and now can install our plug & play devices in both old and new structures. As commercial real estate is the largest consumer of energy in the world, we are determined to impact it the same way the Google Nest smart thermostat did the residential market. We are focused on delivering a first-of-its-kind climate experience to empower hospitality brands and eliminate peak electricity demands for our clients.

During 2020 we will collaborate with air conditioning giant Trane in developing our platform for large chiller plant climate systems, and work with an American utility company on perfecting our utility-facing properties, to maximize efficiency on their side of manufacturing electricity, both projects backed by the State of New York.

Developed and made in Israel, with offices in Israel and the US.

FOUNDED
November 2015
EMPLOYEES
15
BUSINESS MODEL
B2B
OFFERING TYPE
Hardware, Software
FUNDING STAGE
Series A
BUSINESS STAGE
Launched
TOTAL FUNDING
$8.76 Million
SECTORS
Climate Sensor Smart Home

Funding Rounds

Date Announced

Funding Round

Amount Raised

Investors

April 2020
Series A
$5.3 M

AI Technology Stack

AI DESCRIPTION

We are currently training our system to learn each user’s use patterns, routines, and climate comfort preferences.

Also connecting to Building Management Systems, the platform takes into account schedules, room thermal profiles and the technical profiles of end-units to orchestrate and optimize heating and cooling. While user comfort and preferences remain a constant, the system will gradually improve efficiency based on climate meta-data, and with the help of our utility facing features.

AI APPLICATION
Vertical AI
AI TYPES
Deep Learning