Unrivalled accuracy
Validated against real future outcomes on standard datasets. The model produces a fully calibrated risk distribution — proving economically superior to standard methods, with the tail finally visible.

Reserving and capital modelling still rely on legacy methods, yet risk complexity has moved on. Intellegri is powered by the Big Hypotheses Model — a defence-grade Bayesian system originally built to forecast complex, uncertain systems for national security. Transparent decision support that sits alongside your existing models: accuracy, speed, and tail-risk mastery.
Validated against real future outcomes on standard datasets. The model produces a fully calibrated risk distribution — proving economically superior to standard methods, with the tail finally visible.
Patented next-generation acceleration reduces calculation time from months to minutes — making real-time portfolio analysis finally possible.
Superior insight at a fraction of current spend. Decision-grade accuracy without the heavy overhead of legacy consulting — transforming capital efficiency and making advanced modelling affordable.
Designed to understand how uncertain systems evolve as new information arrives — with unparalleled insight into the extreme scenarios that drive capital and strategic decisions. A glass-box methodology delivering a live, probabilistic view of your business.
Move from retrospective analysis to live intelligence. Update capital and reserving positions instantly as new data emerges — results in minutes rather than months.
Glass-box methodology. Unlike black-box AI, Bayesian inference provides explainable reasoning behind every output — improving trust and auditability with regulators and boards.
Built on 12 years of R&D and £44M+ in funding. Patented processes trade model complexity for parallelism — enabling simulation previously considered computationally impractical.
The model adapts as market conditions change — borrowing strength across portfolios to stabilise estimates for sparse data while accurately capturing volatility in complex lines.
More precise modelling unlocks trapped capital and improves pricing and reinsurance optimisation.
A fully justifiable, validated probabilistic foundation that quantifies uncertainty to a defence-grade standard.
"Intellegri's purpose is to make the invisible visible. We are moving the market beyond static actuarial models into a live, adaptive system that can reason, learn, and explain its view of risk — in real time."
Developed by the Signal Processing Group at the University of Liverpool, the Big Hypotheses Model represents a sovereign-scale research programme funded by the UK Government to solve critical national-security challenges. It was built by over 80 post-doctoral researchers to answer questions that cannot be wrong.
Technical edge — Sequential Monte Carlo (SMC) methods within STAN v3, trading model complexity for parallelism: the computational leap that enables real-time Bayesian risk analysis. Insurers, reinsurers and alternative risk-transfer vehicles dynamically update capital adequacy, reserving and exposures as conditions evolve.
Traditional capital models rest on fixed assumptions, periodic recalibration and heavy regulatory overhead. Intellegri replaces this with an intelligent, self-updating system that captures uncertainty as it happens — turning risk management into a live process rather than a retrospective exercise.
Signal Processing Group — origin of the Big Hypotheses Model.
Sovereign-scale programme built for national-security forecasting.
Post-doctoral team assembled to answer questions that cannot be wrong.
Twelve years of research and development behind the platform.
UK startup Intellegri appoints insurance veteran Keogh to Board.
Risk-capital modelling startup Intellegri adds actuarial heavyweight Michel.
A conversation, not a pitch deck. We map your capital challenge to the model's capabilities.
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