CRYLO® Research on AI Managed Crypto Portfolios
CRYLO® Research publishes evidence, methods, datasets, and benchmarks.
Our Research Releases on Crypto Investment Portfolios Fully Powered by AI & ML
Access our insights, methods, data sets, and benchmarks behind CRYLO®. Follow our development and proof of concept, and learn how artificial intelligence combined with machine learning algorithms will change the future of digital wealth management.
Digital Asset Portfolio Research is Our Mission
At CRYLO®, our mission is to make digital-asset investing disciplined, transparent, and accessible. We pair Swiss-grade governance with artificial intelligence (AI) and machine learning (ML) to build crypto portfolios that emphasise risk management, clear rules, and user control of custody.
This research hub documents how we measure, validate, and improve these portfolios—so developers, journalists, and regulators can evaluate our work on its merits.
Our team of researchers look forward to your questions, comments, or feedback. Please feel free to contact us at any time.
Latest AI Crypto Portfolio Research Releases & Benchmarks
Discover what’s new in CRYLO® Research on AI for digital asset portfolio construction.
Our Research Capabilities on AI Wealth Management
Our capabilities distill how we turn research into verifiable outcomes. Here you’ll find the domains we focus on—AI/ML methods, crypto market structure, evidence generation, compliance, and more—each tied to datasets, benchmarks, and clear reproduction steps. Browse the points below to see what we study, how we test it, and where to dive deeper.
AI & ML Research
We design and evaluate model families for trend, regime, and risk-state detection. Emphasis on reproducible metrics, out-of-sample validation, and guardrail performance—not tuning tricks.
Crypto Research
Market structure, liquidity, funding dynamics, and stablecoin behaviour—studies that inform our eligible universe and risk budgets across venues and assets.
Evidence Lab
Independent, code-driven evaluations. Every claim maps to a metric, dataset slice, and commit. We publish negative results and known limitations alongside improvements.
Analytical Research
Methodical analysis of drawdowns, volatility targeting, turnover, slippage, and implementation shortfall. Results are presented with confidence intervals and stress scenarios.
Compliance Research
Non-custodial architecture, jurisdictional eligibility filters, and audit trails. We document what is enforced, how it’s tested, and where constraints may apply.
Model Portfolios
Risk-tiered reference portfolios with clear rules, rebalance logic, and monitoring states. Each portfolio links to relevant methods, datasets, and benchmark results.
Security & Transparency
Design notes on permissions, logging, and tamper-evident records. We publish transparency reports and verification paths without disclosing sensitive configurations.
Data Engineering & Tooling
Pipelines, schema governance, and open utilities (metrics library, stress injectors). Where possible, we provide code examples and DOIs for versioned releases.
How to use our research hub
- Start at Methods to understand the framework.
- Pull the latest Datasets and Benchmarks to verify outcomes.
- Consult Model-Cards for scope and limitations.
- Check Notes for recent updates and ablations.
Citations & Versions
Most artifacts include DOIs and changelogs. Please cite the latest version and consult the dataset/benchmark pages for exact checksums and reproduction steps.
Also Read Our Latest News
As we reshape digital wealth management, we write monthly on the latest events in the financial world and news relating to digital assets.