01
Multi-paradigm AI platform
Predictive scoring, symbolic rule engines, expert-system logic and an LLM layer in one architecture.
Confidential concept · Principality of Monaco
Intelligence,
applied to excellence.
An applied-AI research institute for the luxury economy of the Principality: automotive and motorsport, yachting, tennis and elite sport, luxury goods and cosmetics, real estate, wealth, hospitality and marine sustainability. Built, not theorised.
Scroll43°44′N 7°25′E
€0.00T
global luxury spending, 2025
Bain-Altagamma
€0B
personal luxury goods market, 2025
Bain-Altagamma
>0%
of luxury sales from HNWIs
up from 30% in 2019
0
applied-AI institutes serving Monaco's economy
the gap
The institute
Every advanced economy has one.Monaco does not.
MIAI engineers, deploys and governs AI for luxury: automotive and motorsport, yachting, tennis and elite sport, luxury goods and cosmetics, real estate, wealth, hospitality and marine sustainability, to the standards of discretion, precision and quality the Principality demands.
Mission
Make Monaco the reference point where the luxury economy engineers, validates and governs its AI.
Model
Applied research plus build-and-deploy plus advisory. Three revenue engines, not one.
Anchor
Cooperation with the International University of Monaco.
Team
~10: AI/ML engineers, agent builders, UX/UI, applied researchers, luxury-market lead.
Location
Office in Monaco. Working language: English.
References
ZHAW Centre for AI, TNO, Alexandra Institute, adapted to Monaco's scale.
Priority verticals
Where the Principality's economy meets applied AI
Lead vertical
High-performance automotive is, in engineering terms, a real-time data problem, exactly where applied AI produces measurable advantage.
Telemetry & race strategy
Pit-stop timing, tyre and fuel strategy, undercut decisions
Time-series, RL, Monte-Carlo
Predictive maintenance
Power-unit, gearbox and brake wear before failure
Sensor-fusion, anomaly detection, RUL
Aerodynamics & design
Accelerated CFD and setup optimisation
Physics-informed ML, surrogates
Driver & performance
Racing-line, braking points, fatigue monitoring
Computer vision, sequence models
Manufacturing quality
Automated inspection of components and composites
Vision defect detection, edge inference
Client supply chain
How value flows
Hover a stage to preview it, click to open the full picture. MIAI sits in the middle of the chain and captures revenue at build and deploy, with recurring value from maintenance, iteration and advisory.
Stage 02
MIAI
The institute runs the applied research: benchmark the problem, choose between predictive models, symbolic rule engines and agentic LLM layers, and prove value on a contained pilot before anyone commits to a rollout.
What MIAI does here
Three engines in one house: applied research, build and deploy, strategy and advisory, with IUM as the academic anchor.
Pilot to decision in one quarter
Leadership
Founder & Director
N.J. Berky
The institute needs a director credible at three tables at once: the Monaco luxury environment, the engineering team, and the client boardroom.
Visit njb-berky.com
- Monaco
- BBA, International University of Monaco. Studied, lived and worked in the Principality.
- AI architecture
- Three years as an AI product architect: predictive ML, symbolic rule engines, LLM agents in production.
- Governance
- Red-teaming and safety evaluation; responsible-AI and EU AI Act awareness.
02
Industrial drawings-to-prototype
Computer-vision extraction from engineering documents plus an autonomous configuration agent.
03
B2B AI configurator
Agentic product configurator running on a live manufacturer sales process.
04
Legal-AI platform
Case-centric reasoning: ingestion, retrieval over legal corpora, structured drafting.
05
Heritage AR application
Multi-language visitor app with AR, 360 capture and generative before/after imaging.
06
AI safety evaluation
Structured red-teaming and failure-mode analysis in sensitive domains.
Founding triangle
Partners
Next step
A short online meeting,then a feasibility note.
Align on appetite and priority verticals, then a focused note: first pilot clients, lean-launch cost, and the shape of an IUM cooperation.