Grid Raven's management team comes from the Transmission System Operator world. We combine sector know-how with proven competences in machine learning.

Grid Raven's story began when we noticed that renewable energy developers consistently pointed out that they're having difficulty obtaining grid connections. In sunny and windy places the grid is full, yet at the same time neighboring regions continue to burn fossil fuels. The energy transition has barely started, but power grids are already becoming a bottleneck.

We knew that the existing power grid is not used to its maximum potential. It's possible to safely transmit up to one third more power through the existing network by accounting with real-time and forecast conditions along the line. But existing solutions depend on installing hardware, which is costly, unreliable and slow.

The insight that prompted us to launch the Grid Raven was that machine learning can do Dynamic Line Rating more accurately than physical sensors can. The key is to predict weather conditions down to the meter-level but at the scale of national power grids.

Management team

Markus Lippus
Chief Data Scientist

Previously co-founder and Data Science Lead at Mind Titan, a machine learning agency. Has built over 100 machine learning solutions from the architecture and code down to the physical servers.

Georg Rute
Chief Executive Officer

Previously Head of the Smart Grid Unit at Elering, Estonia's national grid, and founder of Sympower, a demand response aggregator with over 1.5GW of flexibility in the portfolio.

Henri Manninen, PhD
Chief Technology Officer

Previously Digitalisation Team Lead at Elering, responsible among other things for condition assessment of overhead lines, grid modeling and data acquisition. PhD in transmission overhead lines.

Our values are curiosity, integrity and humour.

We love finding stuff out and to get to the bottom of things. We take ownership for what we do and do things well. We can easily admit mistakes, especially if we can laugh about it.

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