Grid Edge RecapJune 27th, 2016 by
ENERGYWORX MAKES ITS PRESENCE KNOWN
After four years of data domination in Europe, Energyworx has expanded to the US market to help her customers battle the same challenges brought on by the energy transition. In June of 2015, Energyworx opened an office in downtown San Francisco and started building out the team and company for growth in North America. The last 12 months has featured pilots and consulting engagements but the time was right to tell the (Grid Edge) World that we are ready to play on the big stage, literally.
On the morning of June 22nd, Energyworx Founder & Chief Visionary Officer stepped on stage in front of hundreds of Energy Leaders to proclaim the benefits of using pure play cloud for crunching large volumes of smart grid data. His message could be summarized in three key points.
- Energy companies need to transition from commodity driven business models to data driven business models
- Cloud computing is a very mature industry with big data tools and platforms that are highly relevant for the energy industry
- Google is the only organization offering truly pure play cloud services
With these three points combined, the Energyworx strategy is revealed: We are building a software as a service running on the latest cloud platform technologies, adding industry specific knowledge and tooling for all our customers.
Or put more simply, Energyworx is disrupting the space with both technology and pricing.
With these bold claims, it helps to have someone backing you up and who better than Google itself. Director of Google Cloud Platform, Dan Powers joined Edwin on stage to explain how Google approaches cloud differently and what this means for the Energyworx value proposition.
Dan explained how GCP developed over time, moving beyond Virtualized Servers and into Automated Services and Scalable Data. He finished the presentation by tackling one of the hottest “buzzwords” of the year: Machine Learning.
Energyworx has been offering cloud based Machine Learning to her customers over the last several months and is able to achieve the highest performance at the lowest cost by building on what Google already has. And why does Google have the best Machine Learning capabilities? As Dan explained, Machine Learning is based on training with examples and the larger the training sets, the more capable the models will be. Who do you think has the largest datasets?
With that, Energyworx and Google walked off stage and challenged the entire room to ingest and analyze data 50-100x faster than their current solutions with at least 75% lower investment. Add in an appearance by Elvis, and the curiosity from the market kept the Energyworx booth bustling throughout the entire event. Many organizations are still wrestling with the ingestion of a diversity of massive data sets and need solutions that can scale instantly to satisfy their business needs.
Thankfully we’ve been there, done that…