Core capability demonstrated across GEiMS (state estimation), ARMOUR (power quality monitoring), GridTIMES (topology identification), and the GridEye SME-1 project.
DEPSYS SA
Swiss SME developing GridEye, a smart grid platform for real-time distribution network monitoring, optimization, and peer-to-peer energy trading.
Their core work
DEPsys is a Swiss cleantech SME that develops GridEye, a software platform for real-time monitoring, control, and optimization of electrical distribution networks. They specialize in making power grids smarter — from state estimation and fault detection to flexibility management and peer-to-peer energy trading. The company systematically uses Marie Skłodowska-Curie (MSCA) fellowships to host researchers who advance specific GridEye capabilities, effectively building an R&D pipeline through EU-funded talent. Their work sits at the intersection of power systems engineering, machine learning, and distributed optimization.
What they specialise in
Central theme in GiFlex (flexibility services), GiSTDS (transactive systems), MNRG (multi-energy reconfiguration), and GEHEMS (home energy management).
GiSTDS focused on scalable transactive distribution with double auction P2P trading; GEHEMS explored agent-based distributed control.
GEHEMS targeted home energy management with IoT and appliance scheduling; MNRG addressed multi-energy system optimization.
GridTIMES (2022-2024) applied complex network theory and GIS data combined with smart meter information for grid topology identification.
How they've shifted over time
DEPsys started (2017-2019) with foundational grid intelligence — state estimation, phasor measurement units, and measurement error correlation — essentially teaching their GridEye platform to understand what's happening in distribution networks. From 2020 onward, the focus shifted decisively toward action and optimization: P2P energy trading, flexibility management, home energy management, and multi-energy systems. The most recent project (GridTIMES, 2022) moved into grid topology identification using complex network theory and AI, suggesting a push toward autonomous grid self-awareness.
DEPsys is moving from passive grid monitoring toward active, AI-driven grid management — making them increasingly relevant for projects involving decentralized energy markets and autonomous distribution systems.
How they like to work
DEPsys overwhelmingly leads its projects — 8 of 10 as coordinator — which is unusual for an SME and reflects a company that drives its own R&D agenda rather than joining others' consortia. Their dominant use of MSCA Individual Fellowships (6 projects) reveals a deliberate strategy: they host post-doctoral researchers to tackle specific GridEye development challenges, effectively using EU mobility funding as an R&D pipeline. With 19 partners across 9 countries, they maintain a moderately broad network but are clearly the hub, not a spoke.
DEPsys has collaborated with 19 unique partners across 9 countries, primarily through MSCA fellowship hosting arrangements where international researchers bring their home institution connections. Their network is European in scope but structured around bilateral researcher exchanges rather than large multi-partner consortia.
What sets them apart
DEPsys is rare among SMEs: a product company (GridEye) that systematically uses MSCA fellowships to fund its R&D, with each fellowship advancing a specific product capability. This means they combine commercial focus with deep academic collaboration — a partner who can both publish papers and deploy software on real grids. For consortium builders, they bring a proven smart grid platform that has been validated across 10 EU projects covering monitoring, optimization, and energy trading.
Highlights from their portfolio
- GiSTDSHighest-funded project (EUR 203,149) tackling scalable P2P energy trading with real-time decision making — the most commercially forward-looking of their portfolio.
- GridTIMESTheir most recent project (2022-2024) combining complex network theory with GIS and smart meter data for automated grid topology identification — signals their next strategic direction.
- ARMOURApplied machine learning and signal processing to power quality monitoring, demonstrating DEPsys's expansion from grid state estimation into predictive condition monitoring.