Virtual Power Systems
Software · California, United States · 11-50 Employees
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Overview
Headquarters
691 S Milpitas Blvd Ste 215, Milpitas, C...Phone Number
(866) 877-7115Website
www.virtualpowersystems.comRevenue
$9 MillionIndustry
ZI Rank: 1
Signal Type
Dec
Jan
Feb
Mar
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May
ZI Rank
2
1
1
1
1
1
About Virtual Power Systems
Virtual Power Systems, headquartered in Milpitas, California, and established in 2012, is an energy control software company. Their platform collects data from infrastructure devices in real-time, making changes to the devices' operation based on machine learning algorithms that optimize power utilization.Explore more
Virtual Power Systems Org Chart
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Revenue
Number of Employees
Type
Funding
Founded In
Virtual Power Systems
$9M
11-50
Private
$40.6M
2013
WS
Wade SchottSenior VP, Customer Solutions & Partnerships
Company Profile Activity
Activity Insights
Virtual Power Systems is experiencing very low activity levels compared to other companies in the Software sector.
What does this means?
Virtual Power Systems is drawing exceptional interest within the Software industry, suggesting notable developments or strong market momentum, learn more about Virtual Power Systems.
Virtual Power Systems financials insights
Gather financial insights about Virtual Power Systems, including details on funding rounds, investors, total funding, and acquisitions, to gain a comprehensive understanding of their financial strategy.
2014
Private Equity
$1.6M
2016
Series A
$4.2M
Private Equity
$5.5M
2019
Series B
$17M
2020
Debt
$350K
Unspecified
$12M
Virtual Power Systems Tech Stack
A closer look at the technologies used by Virtual Power Systems
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Funding
Funding
Virtual Power Systems has received an SBA PPP loan for $350,000-1 million from Silicon Valley Bank, supporting the retention of 20 jobs.
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Frequently Asked Questions Regarding Virtual Power Systems
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Virtual Power Systems, headquartered in Milpitas, California, and established in 2012, is an energy control software company. Their platform collects data from infrastructure devices in real-time, making changes to the devices' operation based on machine learning algorithms that optimize power utilization.... Read More
