Central to all three projects — ATLASS (smart surfaces), OPENMIND (medical devices), and TEESMAT (battery materials) — all require inline measurement and quality monitoring.
IN-CORE SYSTEMES
French SME providing real-time, non-destructive material characterization and inline quality control for advanced manufacturing and energy storage.
Their core work
IN-CORE SYSTEMES is a French SME specializing in advanced material characterization and in-line quality control systems for manufacturing. They develop real-time, non-destructive characterization technologies that allow manufacturers to monitor and control material properties during production rather than after. Their work spans diverse manufacturing domains — from printed organic electronics and custom medical devices to electrochemical energy storage materials — always contributing their core competence in measurement, data-driven process control, and material modelling.
What they specialise in
TEESMAT explicitly lists non-destructive characterization; OPENMIND involves statistical process control for varying lot sizes in customized manufacturing.
OPENMIND keywords include data mining, similarity algorithms, and statistical process control; TEESMAT involves material modelling — both require data-driven decision tools.
TEESMAT (2019-2022) focuses on open innovation test beds for battery materials, including battery safety and regulation compliance.
ATLASS involved printed organic transistors for large-area surfaces; OPENMIND involved micro-pullwinding of fibre reinforced plastics — both demand precise process monitoring.
How they've shifted over time
ICS began in the mid-2010s working on process monitoring for advanced manufacturing — printed electronics (ATLASS) and customized medical device production (OPENMIND), focused on quality control in complex, small-lot manufacturing. By 2019, they shifted toward energy storage materials with TEESMAT, applying their characterization expertise to battery materials, safety testing, and regulatory compliance. This evolution shows a company moving from bespoke manufacturing support toward the higher-volume, higher-demand energy storage sector while retaining their core measurement competence.
ICS is pivoting their inline characterization expertise toward the booming battery and energy storage sector, making them a relevant partner for Gigafactory quality control and battery safety projects.
How they like to work
ICS operates exclusively as a consortium participant, never as coordinator — consistent with a specialist SME that brings targeted technical capabilities rather than project management. With 46 unique partners across 16 countries in just 3 projects, they work in large, diverse consortia (averaging 15+ partners per project). This suggests they are comfortable integrating into big collaborative efforts and adapting their tools to different application domains.
Despite only 3 projects, ICS has built a broad network of 46 partners across 16 countries, indicating involvement in large pan-European consortia. Their reach spans a significant portion of EU member states, typical for Innovation Action and Research projects in manufacturing.
What sets them apart
ICS occupies a specific niche: they are a measurement and characterization company that can plug into almost any advanced manufacturing or materials pipeline. Unlike large testing labs, they focus on real-time, in-line solutions — meaning their technology works on the production floor, not in a separate lab. Their ability to cross domains (electronics, medical devices, batteries) with the same core characterization competence makes them a versatile integration partner for any consortium needing inline quality assurance.
Highlights from their portfolio
- TEESMATMost recent project, signals strategic pivot into electrochemical energy storage — an open innovation test bed with high industry relevance for battery manufacturing scale-up.
- OPENMINDLargest EC contribution (EUR 590,025) and most technically diverse — combining fibre reinforced plastics, micro-pullwinding, data mining, and statistical process control for personalized medical devices.