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Estimated annual value


less effort spent on data management tasks

Grid operations have an industrial data problem

Operators today have an abundance of static and dynamic operational data but little means to efficiently use it to answer key questions about grid networks and assets, resulting in limited total operational visibility. The process to collect and analyze this data, and then implement new workflows continues to be challenging due the following reasons:


Siloed industrial data

Structured and unstructured data remain in disparate systems such as historians, ERP, CMMS, etc., making it difficult to find, access, and use

Lack of context

Data relationships remain largely unmapped, putting the burden on domain experts to understand and interpret what the data means

Inability to scale use cases

Analytics use cases are developed individually at high cost and with little repeatability because scaling today is largely a manual process