EEme (Pittsburgh, USA) EEme’s proprietary analytics engine converts raw smart meter data into appliance level energy insights. This is easily integrated into utilities‘existing platforms through EEme’s API.
Read more on www.energyefficiency.me
Spotlight Q&A with EEme
Describe your startup and product as if you were describing it to a non-tech person on the street.
We bring the scalable analytics element to the building energy efficiency industry by converting existing smart meter data into appliance/equipment-level energy insights using our proprietary machine learning algorithms without requiring any user intervention or new hardware.
Describe how you got the idea to start your business.
Every energy industry has a data-driven approach to quantifying opportunities across different site (think “heat maps” for wind energy!). We leverage existing smart meter data to quantify energy efficiency opportunities across buildings and appliances.
How does your product/service works?
Any organization, e.g., electric utilities, 3rd party energy efficiency service, software or hardware providers, who owns smart meter data can send their data to our cloud-based “Disaggregation-as-a-Service” engine to retrieve appliance-level energy insights almost instantaneously to plug them into their existing platforms, for which we charge a subscription fee on a per meter per year basis.
Why did you apply for the Next Step Challenge program?
We were enticed by SE’s interest in providing participants a testbed of 270K smart-metered customers they service in their territory.
Recent big news?
We are preparing to release another major 3rd party validation report which will be announced via high-profile energy news outlets. Stay tuned!
Who is the founder(s) of your team?
Dr. Enes Hosgor, CEO & Founder
Current number of employees.
5 full-time + 5 interns
Which countries are you from?
Turkey, China, United States
Year Founded: 2013
Contact details: firstname.lastname@example.org