SciTransfer
Organization

FUNDACION INSTITUTO DE INVESTIGACION INNAXIS

Madrid research foundation specialized in air traffic management analytics, aviation safety intelligence, and ML-powered flight decision support tools.

Research institutetransportESNo active H2020 projects
H2020 projects
12
As coordinator
3
Total EC funding
€3.8M
Unique partners
47
What they do

Their core work

INNAXIS is a Madrid-based research foundation specialized in air traffic management (ATM) analytics, complexity science, and data-driven aviation safety. They build simulation models, decision-support tools, and data platforms that help airlines, air navigation service providers, and policymakers understand and improve the European aviation system. Their work spans from long-term strategic forecasting (European travel demand in 2050) to operational tools like go-around prediction and flight dispatcher advice powered by machine learning.

Core expertise

What they specialise in

Air traffic management analytics and simulationprimary
8 projects

Core to nearly all projects including Vista, Domino, Engage, Modus, SafeOPS, and Pilot3 — all focused on ATM performance, coupling, and decision support.

Aviation safety intelligence and data-driven riskprimary
3 projects

SafeClouds.eu (their largest project at EUR 1.1M as coordinator), OPTICS2, and SafeOPS all target safety analytics using flight data and ANSP records.

Agent-based modelling and complexity sciencesecondary
2 projects

Domino explicitly used agent-based modelling to evaluate ATM system coupling; DATASET2050 applied system-level modelling to forecast European travel.

Machine learning for flight operationsemerging
2 projects

Dispatcher3 applied ML to flight planning using historical data, and SafeOPS used automated prediction for go-around decisions and controller support.

Transport policy and innovation ecosystemssecondary
3 projects

CAMERA coordinated mobility research assessment, SeeRRI explored responsible innovation in regional development, and Engage built the SESAR knowledge transfer network.

Evolution & trajectory

How they've shifted over time

Early focus
ATM coordination and knowledge infrastructure
Recent focus
ML-powered flight decision support

In their early H2020 period (2014–2018), INNAXIS focused on strategic coordination and knowledge infrastructure for European aviation — building roadmaps, knowledge hubs, and the SESAR transfer network (Engage, CAMERA, DATASET2050). From 2019 onward, their work shifted decisively toward applied, data-intensive tools: machine learning for flight planning (Dispatcher3), automated decision support for controllers (SafeOPS), and intermodal transport modelling (Modus). The trajectory shows a clear move from observatory and coordination roles toward hands-on, AI-powered operational tools.

INNAXIS is moving from studying and mapping the ATM system toward building predictive, data-driven tools that directly assist pilots, dispatchers, and controllers in real-time operations.

Collaboration profile

How they like to work

Role: active_partnerReach: European15 countries collaborated

INNAXIS operates as both a project leader and a reliable consortium partner — they coordinated 3 of their 12 projects (25%), including their largest (SafeClouds.eu), while contributing specialist expertise in the remaining 9. With 47 unique partners across 15 countries, they maintain a broad European network rather than repeatedly working with the same groups. This makes them a well-connected hub in the SESAR/ATM research community, easy to integrate into new consortia.

INNAXIS has collaborated with 47 distinct partners across 15 European countries, reflecting deep integration into the SESAR and EU aviation research ecosystem. Their network spans universities, ANSPs, airlines, and aviation technology companies across the continent.

Why partner with them

What sets them apart

INNAXIS occupies a rare niche: they combine complexity science and agent-based modelling with practical aviation data analytics — a bridge between academic ATM research and operational tool-building. Unlike large aerospace companies, they are agile enough for exploratory research; unlike universities, they deliver applied decision-support systems. Their progression from coordination/observatory projects to ML-powered operational tools makes them an increasingly valuable partner for anyone building the next generation of ATM automation.

Notable projects

Highlights from their portfolio

  • SafeClouds.eu
    Their largest project (EUR 1.1M) as coordinator, directly addressing aviation safety intelligence through data-driven methods — the clearest expression of their core mission.
  • SafeOPS
    Represents their most advanced work: fusing ANSP and airline data for automated prediction and controller decision support, showing where their expertise is heading.
  • DATASET2050
    Their first coordinated H2020 project, tackling long-range European travel demand forecasting — established them as strategic thinkers in transport futures.
Cross-sector capabilities
Data science and machine learning applicationsComplex systems modelling and simulationInnovation ecosystem governanceIntermodal transport and mobility policy
Analysis note: Strong profile with 12 projects and clear thematic coherence around ATM/aviation. Keywords are available for roughly half the projects; the evolution analysis is well-supported but would benefit from deliverable-level data for the earlier projects that lack keywords.