/experience → clarity /
praXvalue builds and delivers air-gapped open-source AI for high-stakes negotiation.
We partner with institutions that require clarity under uncertainty.
We capture, structure, and operationalize experiential knowledge in environments where data is scarce, uncertain, or politically sensitive.
Grounded in decades of mathematical and AI research for robust decision systems.
Operated in complete isolation from external networks—making and suitable for classified environments and sovereign strategic decisions.
Robust systems built for real-world, high-stakes execution.
decision-intelligence engine for high-stakes environments
eigenmind is a decision-intelligence engine designed to capture, structure, and operationalise expert knowledge in environments where data is scarce, uncertain, or fragmented. Built on three decades of research in optimisation, AI, and risk modelling, it transforms tacit human expertise into reusable decision frameworks while remaining fully air-gapped and computationally frugal. To achieve this, eigenmind combines light, efficient open-source pretrained embedding models for semantic structuring with proprietary semantic-graph construction methods, and uses compact small language models for lightweight, local inference — ensuring high performance without ever compromising security. At its core, eigenmind relies on eigenvalue-based optimisation across semantic graphs to reveal structure, surface insight, and support robust decision-making.
Transforms tacit expertise into structured, reusable decision frameworks
Fully isolated and computationally frugal for sensitive environments
Reveals intrinsic structure hidden within complex systems
Built for defence, finance, and high-stakes decision domains
François Oustry is an applied mathematician and entrepreneur specialising in decision-making under uncertainty. A graduate of ENSTA Paris and Stanford, he earned a PhD in convex optimisation funded by the DGA (French Defence Procurement Agency), followed by a postdoctoral fellowship at NYU’s Courant Institute. He was then recruited as a researcher at INRIA (National Institute for Research in Digital Science and Technology) before founding his first company Raise Partner — a financial risk-management technology firm. Over more than three decades, he has designed advanced optimisation and AI systems for global financial institutions, sovereign organisations, and strategic operators working in complex geopolitical environments. He later co-founded a quant-NLP hedge fund, Suzugia, acquired by AllianceBernstein — and delivered high-reliability analytical platforms to institutional investors, sovereign wealth funds, and operational teams in sensitive, high-uncertainty contexts. He is currently CEO of praXvalue, where he develops open-source, sovereign AI capabilities — including the air-gapped intelligence engine /eigenmind/ — supporting negotiators, defence communities, and organisations facing heightened geopolitical uncertainty.
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