SciTransfer
Organization

COMPAGNIE EUROPEENNE D'INTELLIGENCE STRATEGIQUE

Belgian strategic intelligence SME specializing in threat analysis, scenario modeling, and cyber-physical security for critical infrastructure and border control.

Innovation consultancysecurityBESMENo active H2020 projectsThin data (2/5)
H2020 projects
2
As coordinator
0
Total EC funding
€720K
Unique partners
47
What they do

Their core work

CEIS is a Belgian-based strategic intelligence and security consulting firm specializing in risk analysis, threat assessment, and security system design for public-sector and critical infrastructure clients. In EU research projects, they contribute expertise in identifying threats, modeling scenarios, and translating security intelligence into operational recommendations — the bridge between raw data and decision-maker action. Their project work spans border control human performance (BODEGA) and data-driven safety for metro and railway networks (SAFETY4RAILS), suggesting a core capability in applied security analysis across both physical and cyber-physical domains. They are not a technology builder but a knowledge integrator: they bring the intelligence tradecraft, scenario-building, and end-user understanding that technical partners lack.

Core expertise

What they specialise in

Strategic security intelligence and risk analysisprimary
2 projects

Both BODEGA and SAFETY4RAILS required scenario modeling, threat forecasting, and mitigation strategy design — the analytical core of what a strategic intelligence firm provides.

Cyber-physical security for transport infrastructureprimary
1 project

SAFETY4RAILS (2020-2022) focused on combined cyber-physical threat detection, anomaly forecasting, and innovative mitigation strategies for trans-modal metro and railway systems.

Border security and human performance in control systemssecondary
1 project

BODEGA (2015-2018) addressed proactive enhancement of human performance in border control, implying expertise in operational security design and human-factors analysis.

End-user requirements and what-if scenario analysissecondary
1 project

SAFETY4RAILS keywords explicitly include 'end-user focused' and 'what-if-cases', suggesting CEIS played the role of translating operational needs into system requirements.

Evolution & trajectory

How they've shifted over time

Early focus
Border control human performance
Recent focus
Cyber-physical transport security analytics

In the early period (BODEGA, 2015-2018), CEIS was engaged in border security with a focus on human operators — how personnel perform under pressure, how to enhance their decision-making in control environments. No technology-specific keywords were captured from that phase, pointing to a predominantly analytical and consulting role. By the later period (SAFETY4RAILS, 2020-2022), the focus had shifted clearly toward data-driven, cyber-physical security: anomaly detection, forecasting, and structured mitigation strategies for complex transport infrastructure. The trajectory shows a deliberate move from human-centric border security toward algorithmic and system-level security intelligence for critical infrastructure.

CEIS is moving toward data-driven security intelligence for critical infrastructure, making them a relevant partner for projects combining AI-based threat detection with operational security in transport, energy, or urban systems.

Collaboration profile

How they like to work

Role: specialist_contributorReach: European14 countries collaborated

CEIS has never led an H2020 project — they join as a participant, likely in the role of security intelligence expert within large, multi-partner consortia. With 47 unique partners across just 2 projects, they operate in broad, diverse consortia (averaging over 20 partners per project), which is typical for RIA and IA security projects where no single actor covers the full chain. This suggests they are comfortable working within complex multi-stakeholder structures and are valued for a specific, bounded contribution rather than overall project leadership.

CEIS has built connections with 47 unique partners across 14 countries through just two projects, indicating involvement in large, pan-European security consortia. Their network likely spans research institutes, technology firms, public authorities, and transport operators — the typical composition of EU security RIA/IA projects.

Why partner with them

What sets them apart

CEIS fills a gap that pure technology firms cannot: they bring strategic intelligence methodology — scenario planning, threat forecasting, and what-if analysis — into technically-heavy EU security projects. Where engineers build the detection systems, CEIS defines what threats to look for and what the response options mean in operational practice. For consortium builders in transport security, border management, or critical infrastructure protection, CEIS offers the intelligence tradecraft layer that turns sensor data and algorithms into actionable security decisions.

Notable projects

Highlights from their portfolio

  • BODEGA
    Their first H2020 engagement and largest grant (EUR 438,625), focused on the human dimension of border control — an uncommon angle that positioned CEIS as a behavioural and operational security expert rather than a pure technology firm.
  • SAFETY4RAILS
    Represents a strategic pivot toward data-driven cyber-physical security for metro and railway systems, with CEIS contributing anomaly detection frameworks and end-user-focused mitigation strategies — evidence of deliberate portfolio evolution.
Cross-sector capabilities
transport safety and infrastructure protectiondigital security and anomaly detection systemspublic authority risk management and crisis response
Analysis note: Only 2 projects in the dataset, with no keywords recorded for the earlier BODEGA project. The profile is directionally reliable but thin — the expertise areas and evolution narrative are grounded in the available data but would benefit significantly from access to project deliverables, CEIS's own website content, or additional project history outside H2020.