Vehicle predictive maintenanceprimary
2 projects
Both Jam (Phase 1) and JAM (Phase 2) focus on predicting vehicle failures using real-time data and AI to reduce downtime and maintenance costs.
Organization
STRA, SA
Portuguese SME developing AI-powered predictive maintenance for vehicle fleets, reducing downtime through real-time data analytics.
Technology SMEtransportPTSMENo active H2020 projectsThin data (2/5)
H2020 projects
3
As coordinator
2
Total EC funding
€1.4M
Unique partners
9
What they do
Their core work
Stratio is a Portuguese technology SME that develops AI-powered predictive maintenance solutions for vehicle fleets. Their core product uses real-time sensor data to forecast mechanical failures, reduce downtime, and cut maintenance costs for transport operators. They also contribute to intelligent mobility research, participating in projects that improve the passenger travel experience in rail and public transport.
Core expertise
What they specialise in
AI / machine learning for transportprimary
2 projects
JAM explicitly applies artificial intelligence to fleet maintenance, and the Phase 1 feasibility study validated the technical approach.
Intelligent mobility and passenger systemssecondary
1 project
My-TRAC (My TRAvel Companion) addresses smart travel assistance under the Shift2Rail programme.
Evolution & trajectory
How they've shifted over time
Early focus
Vehicle predictive maintenance AI
Recent focus
Intelligent transport systems
Stratio's H2020 participation spans a short window (2016–2020) but shows a clear SME growth trajectory. They started with the SME Instrument Phase 1 feasibility study for their predictive maintenance platform, then secured Phase 2 funding to develop the full product — a classic scale-up path. Their participation in My-TRAC (Shift2Rail) in 2017 suggests an early move to broaden from fleet maintenance into wider intelligent transport applications.
Stratio appears to be expanding from a niche fleet maintenance product into broader smart transport and mobility solutions, making them relevant for future multimodal transport projects.
Collaboration profile
How they like to work
Role: consortium_leaderReach: European4 countries collaborated
Stratio predominantly leads its own projects — coordinating 2 out of 3 H2020 projects, both through the SME Instrument which funds single-company innovation. Their one consortium participation (My-TRAC under Shift2Rail) shows willingness to join larger research collaborations when the topic aligns. With only 9 unique partners across 4 countries, they are a focused operator rather than a networking hub.
A compact network of 9 partners across 4 countries, mostly built through a single Shift2Rail consortium. Their coordination experience is primarily solo SME Instrument work rather than large multi-partner projects.
Why partner with them
What sets them apart
Stratio occupies a specific niche at the intersection of AI and fleet maintenance — a combination that few European SMEs focus on exclusively. Their successful progression from SME Instrument Phase 1 to Phase 2 signals that the EU evaluators saw genuine market potential in their technology. For consortium builders in transport or smart mobility, they offer a product-oriented SME with real deployment ambitions rather than purely academic research.
Notable projects
Highlights from their portfolio
- JAMLargest funding (EUR 1.1M) through SME Instrument Phase 2 — indicates a validated product with commercialization potential in vehicle predictive maintenance.
- My-TRACShift2Rail participation shows Stratio can integrate into major EU rail research initiatives beyond their core fleet maintenance product.
Cross-sector capabilities
Industrial IoT and sensor analyticsAI-based predictive maintenance (applicable to manufacturing)Fleet management and logistics optimization
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