Services
Five related areas of practice.
Each engagement is scoped to the depth the question requires - from a written assessment to a system in production.
Decision & Risk Modelling
Some decisions are too expensive to make on intuition. The work here is the formalisation of stochastic problems and the construction of probabilistic models - Bayesian, hierarchical, calibrated to the client's domain and data - with decisions derived under explicitly stated uncertainty. Methods include stochastic calculus, MCMC, extreme-value theory, Monte Carlo simulation, and time-series analysis.
Outcome A decision with its confidence stated, and a model the client owns.
Technical Due Diligence & Pre-Investment Review
Capital, partnerships, and reputations are committed on the strength of technical claims. Helios examines those claims independently - model validity, data integrity, system architecture - so that investment, partnership, or strategic commitment rests on evidence rather than assertion.
Outcome A clear assessment of what is solid, what is fragile, and what cannot yet be known.
Market Design & Financial Engineering
When a market fails to clear, fails to attract participation, or does not yet exist, the remedy is structural, not promotional. The work is the design and analysis of market mechanics, instruments, and infrastructure: price discovery, risk transfer, order books and dark pools, settlement, clearing, custody, options volatility models, smart order routing, and bespoke derivatives - across centralised, decentralised, and digital-asset markets.
Representative work includes the institutional trading and settlement systems designed for Fusang; Light.cx, the cryptocurrency derivatives platform founded by Dr. Silverman; and algorithmic trading systems in production for institutional clients. Where a design warrants it, the work extends through architecture to production implementation.
Outcome Designs that anticipate commercial reality and regulatory scrutiny.
Applied AI & Data
Most AI initiatives disappoint for the same reason: the data was never going to support the promise. Statistical modelling and machine learning here are governed by the actual information content of data rather than its volume: hierarchical models, classifiers, support vector machines, and textual analysis, with high-performance computing when scale requires it. Engagements frequently begin with an assessment of what the data can and cannot support; where warranted, models are taken through to production systems. Applied domains have included finance, digital advertising, construction, education, and medicine.
Outcome Models that can be defended - technically, commercially, and to a regulator.
Strategy & Board Advisory
Not every question needs a project; some need a person to ask. Strategic framing of complex technical and market questions; product and system concepts that are both ambitious and executable; continuing counsel to CEOs, boards, and investment committees on quantitative, technological, and market-structure questions - including digital assets, a field in which Dr. Silverman has worked since 2011.
Outcome Specialist judgment that remains available when the next difficult question arises.
If a matter falls outside these areas, the response is a referral rather than a stretched definition.