Maplewell™ Energy Joins Intel® Liftoff Program for AI and Machine Learning Startups
The program helps startups innovate and scale.
BROOMFIELD, CO — April 23, 2024 — Maplewell Energy, developer of energy demand optimization and predictive control software for distributed energy storage, today announced it has been accepted in Intel® Liftoff, a program designed to foster and grow technology solutions. Through Intel Liftoff, startups can access the latest AI tools in an open ecosystem, bringing them the computational power they need to solve their most critical technical challenges. The program also serves as a springboard for collaboration where startups can form partnerships to refine each other’s offerings.
“We are thrilled to announce Maplewell Energy as a new member of our startup program! This partnership marks a strategic milestone as we collaborate with some of the most innovative companies in the industry,” said Dr. Eugenie Wirz, Global Community Manager, Intel® Liftoff.
The program will help Maplewell scale its use of advanced technology to balance the grid, supporting both utilities and electricity customers such as commercial enterprises. As electrification and deployment of distributed energy resources (DER) accelerate, the distribution grid is becoming increasingly complex and strained. Enterprises and governments face challenges when adding significant electric load onto the system, and utilities are challenged to handle this increasing load. An effective solution is coupling battery storage with intelligent energy management to eliminate interconnection delays, defer infrastructure upgrades, reduce peak demand costs, and match demand with renewable energy production.
Maplewell is offering this solution with its groundbreaking advanced energy management system, JANiiT, which enhances distributed energy storage performance for optimum peak shaving, load management, and coincident peak reduction. By deploying JANiiT with battery storage as a turnkey solution, Maplewell is optimizing and controlling peak demand for utilities as well as commercial, industrial, and government enterprises. Running 24/7 and built on a high-availability architecture, JANiiT considers over 230 trillion scenarios to determine the optimal dispatch of a battery system, automatically reducing peak events at the customer, distribution, and transmission levels.
“We are honored to team with Intel AI architects and developers on Maplewell’s AI solution. Intel Liftoff will allow us to harness Intel AI tools and top-notch AI domain expertise to accelerate our product roadmap,” said Matt Irvin, CEO & Co-Founder of Maplewell. “This collaboration will not only propel our growth and visibility but will also foster unique connections within the technology ecosystem. We are excited to embark on this journey, leveraging Intel’s extensive resources, tapping into their expert insights, and getting the chance to collaborate with other AI-centric organizations.”
The tools provided by Intel Liftoff will help Maplewell scale and better serve its commercial & industrial and utility customers. Maplewell plans to use the resources available through the program, including Intel tools such as oneAPI Base toolkit, OpenVINO toolkit, and Intel optimized Pytorch and Tensorflow to improve AI performance on Intel Edge and Intel Developer Cloud. The program will also offer Maplewell the opportunity to collaborate with industry-leading experts and other AI-driven organizations.
About Maplewell Energy
Maplewell is modernizing energy demand for commercial and industrial enterprises by unlocking demand flexibility with distributed battery storage to create demand savings, grid service revenue, and energy resiliency. The company’s optimization and predictive control technology enables energy storage solutions behind the meter or in front of the meter. Maplewell’s solution helps solar developers, energy service companies, industrial facilities, and distribution system operators predict, optimize, and control peak demand. For more information, visit https://www.maplewell.energy.
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