SKEION helps research teams, institutions and satellite stakeholders understand critical solar magnetic structures through advanced MHD modelling, AI-assisted interpretation and decision-ready software.
Generic alerts tell you that risk is rising. SKEION is being built to explain where the risk comes from, which magnetic structure carries it, and how it can be explored, documented and acted on.
Illustrative — not an operational signal
Space-weather stakeholders already have access to monitoring, bulletins, indices and alerts. The harder problem is deciding what those signals mean for a mission, a fleet, a research case or a resilience workflow.
Today, many workflows remain fragmented between:
The gap is not data access. The gap is physical interpretation.
Navigation, power and telecommunications can be affected at once. SKEION works on the upstream layer — the physical interpretation of solar risk before it propagates.
SKEION builds a physics-based intelligence layer between solar observations and the decisions that depend on them — transforming complex solar and MHD data into interpretable, shareable and decision-ready outputs.
Magnetograms and solar observation data provide the physical input.
Advanced MHD modelling reconstructs and characterizes critical magnetic structures.
The system helps identify, compare and follow structures of interest.
aiXplore makes complex 3D MHD outputs accessible in the browser.
Reports, event briefs and future API integrations support scientific and operational workflows.
SKEION does not aim to replace existing space-weather centers. It aims to provide a stronger upstream intelligence layer that can support research, institutional analysis and future operational decision-making.
aiXplore helps scientists and institutions inspect complex MHD outputs directly in the browser, without heavy local installation — built for interactive exploration of magnetic structures, coronal topologies and evolving configurations.
Built around MeshMHD, this layer is designed to reconstruct, follow and interpret critical solar magnetic structures with AI-assisted analysis and physical context.
SKEION translates space-weather analysis into outputs teams can use: event replay, mission resilience briefs, anomaly attribution context, institutional reports and future integration-ready APIs.
aiXplore interface
aiXplore helps solar physics and heliophysics teams inspect 3D magnetic structures, compare configurations and share visual evidence without relying only on heavy general-purpose tools.
SKEION can support institutional teams with physically interpretable analysis of pre-eruptive structures, event replay, benchmark datasets and structured reporting.
For satellite teams, the value is not another alert. It is understanding whether a solar event may explain an anomaly, require closer monitoring, or support a mission-readiness decision.
Operators and manufacturers increasingly need to show that natural space-environment hazards are considered. SKEION turns that into automated, self-service evidence — event replay, pre-launch risk reports and anomaly context.
Research published in Nature
At the core of SKEION is MeshMHD, a solar magnetohydrodynamics modelling framework developed at the CPHT through more than 25 years of research led by Tahar Amari, CNRS Director of Research.
This work has led to three publications in Nature, including two cover stories, and enables the reconstruction and characterization of three-dimensional coronal magnetic structures associated with eruptive solar regions. SKEION's role is to transform that scientific depth into usable software: exploration, interpretation, reporting and future operational integration.
Deep physics is not the product by itself. It is the reason the product can be more explainable.
Starts from solar MHD modelling and physical reconstruction, not only statistical correlation.
Focuses on identifiable magnetic structures, not only abstract scores.
Links risk signals to visual and physical evidence that can be inspected and discussed.
Designed to move from exploration to reporting, event replay and future integration.
SKEION is a French deep-tech project at the intersection of solar physics, software and space resilience.
CNRS Director of Research, creator of MeshMHD and author of three Nature publications in solar eruption research. A recognized expert in solar MHD and eruptive magnetic structures, he provides the scientific foundation and physical coherence of SKEION.
Sofiane leads the product, strategy and execution of SKEION. He develops aiXplore and brings together software thinking, product positioning and business execution to turn the scientific foundation into a usable platform.
SKEION is engaging with research labs, institutions, satellite stakeholders and strategic partners interested in physics-based space-weather intelligence.
Contact SKEION to request aiXplore access, discuss an institutional pilot, explore a satellite resilience use case or start a strategic conversation.
SKEION is currently engaging with selected research teams, institutions, satellite stakeholders and strategic partners.