AERAUT capabilities are designed to operate within established aviation technical structures and regulated authority frameworks.
01
Airline Engineering
Engineering divisions responsible for maintenance control, continuing airworthiness, and technical oversight.
Operational environments governed by approved procedures, defined escalation paths, and regulatory compliance obligations.
02
Maintenance & Overhaul
High-volume maintenance organizations operating under structured production control and quality assurance systems.
Environments requiring procedural integrity and continuity of institutional knowledge.
03
Reliability & Technical Services
Reliability management and technical services units overseeing fleet performance, defect analysis, and engineering review processes.
Structured reporting hierarchies and defined engineering authority.
04
Approved Training Organizations
Regulated training environments operating under certification standards and instructional governance frameworks.
Structured competency development and documented progression pathways.
Products
Structured Intelligence Across Three Operational Domains
AERAUT is building three complementary systems designed for aviation technical environments.
Each operates within governed frameworks and established authority structures.
01
Maintenance Execution
Maintenance Execution
A structured intelligence capability embedded within maintenance environments.
Designed to reinforce procedural integrity and support technical decision contexts within approved operational boundaries.
02
Reliability Intelligence
Predictive Maintenance
A governed predictive capability supporting engineering visibility across operational and reliability environments.
Designed to function within defined oversight structures and controlled data contexts.
03
Technical Competency
Technical Competency
A structured framework supporting workforce development within regulated training environments.
Designed to formalize institutional knowledge and align with established training standards.
03Industry Partnership
Advancing trusted innovation across aviation
Strategic Partner
The Aviator Institute (TAI)
AERAUT is collaborating with The Aviator Institute through a structured partnership designed to explore relevant innovation opportunities in aviation environments. The collaboration supports domain feedback, structured evaluation, and the progressive development of practical use cases aligned with real operational needs.
The industry’s answer to the technician shortage is speed. The open question is evidence.
In September we spoke at two conferences: APATS in Bangkok, on aviation training, and PAM APAC in Singapore, on predictive maintenance. They are different communities, but they are heading in the same direction: AI to accelerate training, and AI to turn predictions into decisions. Here is what we take from it.
1.
The shortage is being framed as a speed problem.
McKinsey estimates that the global shortfall of maintenance technicians could reach roughly 22,000 by the end of 2026. It argues that most of the gap expected by 2029 can be closed through productivity, including AI tools and a shorter time to proficiency. APATS reflected the same pressure, with AI and competency-based training at the centre of its programme.
Our read: speed is the right goal, but in a regulated environment it creates a second requirement. Every hour saved in training has to be matched by evidence that a named technician is ready for a specific task at the moment the work is assigned.
Our read: once an AI output informs a maintenance decision, the questions change. Where does this recommendation come from? Is it within the organisation’s approved references? Who is accountable for acting on it? These questions are not details to settle later. They decide whether an AI output can be trusted in a Part-145 or Part-147 environment.
3.
The hard problem is governance, not generation.
Generating an answer is now easy. Keeping every AI suggestion tied to its source, bounded by the organisation’s own references, and subordinate to a qualified person’s decision is not. That is the problem AERAUT works on, and what we are testing with a North African Part-147 training partner.
AI recommends. It does not authorise.
For training and maintenance leaders evaluating AI, three questions to ask any vendor, including us:
Can it show where every suggestion comes from?
Can two instructors’ assessments be compared on the same basis?
Does a qualified person remain the decision-maker on record?
Next, we take this to World Aviation Festival in Lisbon:
Tue 13 Oct, 10:00, Startup Theatre: “AI in Aviation Maintenance: From Automation Hype to Operational Trust”
Thu 15 Oct, 13:50, panel: “Built From Scratch: Insights from female founders”
Stand S35, all three days
Then EATS in Cascais (3–5 Nov) and PAM Europe in Dublin (9–10 Nov).
AERAUT is an aviation technology company focused on structured intelligence systems for technical operations.
The company operates within regulated aviation environments, supporting maintenance, reliability, and competency domains through governed system design.
Our Focus
AERAUT develops intelligence layers intended to operate within established operational frameworks. Its work spans three areas:
Maintenance Execution
Predictive Reliability
Technical Competency Development
Each system is designed to function within defined authority structures and controlled knowledge boundaries.
Operating Context
AERAUT systems are designed for environments where traceability, regulatory alignment, and role-based access are fundamental requirements. Built for:
Airline Engineering Divisions
MRO Organizations
Reliability & Technical Services Units
Training Academies and Part-147 environments
Design Approach
AERAUT systems are built according to the following principles:
Governance-first architecture
Structured data boundaries
Defined operational roles
Sovereign or on-premise deployment options
Every system is designed to align with institutional oversight requirements.
Engagement Model
Engagements begin with structured alignment discussions covering:
Organizational governance
Integration scope
Deployment configuration
Evaluation framework
04 | Strategic Advisory
Trusted guidance from industry leaders
Jean-François
Strategic Advisor
Advisory Board
25 Years
Semiconductor Industry
Investor
Angel & VC Partner
Mentor
Efrei Entrepreneurs
Jean-François is a Business Developer, Sales Entrepreneur and Angel Investor
He has been working for 25 years in the semiconductor industry where he alternated salary experiences as sales contributor (MIPS, Synopsys, Cadence) and entrepreneurial experiences.
He notably co-founded inChip Technology, a microprocessor provider, to improve mobility in motorway tolls.
He supports entrepreneurship and innovation programs through mentoring at Efrei Entrepreneurs, incubator of Efrei Paris and by his presence in several advisory boards.
He's responsible of the Start-up Week, a start thinking program at Efrei Paris (Mastere e-business).
Jean-François is also the co-founder and Managing Partner at Cèdre Ventures, a post-seed investment fund dedicated to the startups of the French Tech.
Latterly he co-founded Efrei Business Angels, an alumni entrepreneurs and Angel Investor association of Efrei Paris.
He is currently Head of Sales at Ciris Semiconductor, a startup aiming to improve Analog & Mixed Signal Design in the semiconductor industry.
Key Affiliations
MIPSSynopsysCadenceinChip TechnologyCèdre VenturesEfrei Business AngelsCiris Semiconductor
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See AERAUT in action
Book a 30-minute walkthrough. We'll walk you through our approach on a reference maintenance scenario and discuss how it applies to your organization.
