Agentic Economics
Researching Multi-Agent Systems (MAS) through the lens of incentive compatibility and game theory.
Modeling how autonomous AI agents optimise resource allocation and governance within complex enterprise ecosystems.
The Haute Intelligence Research Lab bridges pure mathematical theory and enterprise-grade sovereign AI. We define the frameworks that power the next generation of strategic infrastructure.
Haute Intelligence maintains a strategic partnership with the Swiss Quantum Economics AI Lab, an alliance between the discipline of academic research and the velocity of applied infrastructure.
To merge the frontiers of Quantum Computing and Mechanism Design with real-world economic modeling.
Transforming theoretical breakthroughs into scalable primitives for the global digital economy.
Researching Multi-Agent Systems (MAS) through the lens of incentive compatibility and game theory.
Modeling how autonomous AI agents optimise resource allocation and governance within complex enterprise ecosystems.
Moving beyond probabilistic forecasting to causal inference. We develop frameworks using Large Language Models (LLMs) and Graph Neural Networks (GNNs) to build dynamic financial knowledge graphs.
Empowering AI-NEOS to interpret macroeconomic signals and microeconomic drivers with human-level logic.
High-performance algorithmic optimisation for Intelligence at the Edge.
Focusing on stochastic analysis and verifiable computation within the Swiss Subnet infrastructure.
Long-term, high-impact research projects with full access to our proprietary data and Swiss Subnet compute clusters.
Deep-dive implementations focused on algorithmic efficiency or specific financial-agent use cases.
High-intensity research assistantships for final-year students looking to apply theory to production-grade AI.
All selected researchers receive supportive grants. We believe financial independence is a prerequisite for pure, uninhibited innovation.
Mechanism design, game theory, computational finance, microeconomic modeling.
Stochastic processes, optimisation theory, graph theory, quantum logic.
Natural Language Processing (NLP), reinforcement learning, distributed systems architecture.
Submit your interest below. We do not run rolling cohorts; openings are matched to active research questions and available supervision.
Every application is personally reviewed by the Research Director. We value precision, autonomy, and the courage to challenge established paradigms.