Market and flow research grounded in live behavior.
Market structure, cross-asset relationships, trend regimes, liquidity, client flow, and risk behavior.
Systematic digital asset infrastructure
Quantitative
operating layer
for digital asset
businesses.
Mnemex builds the research, models, flow-optimization logic, and production systems that help institutions trade, allocate, and manage treasury without building a full quant team.
For funds, fintechs, brokers, payment businesses, and digital asset operators that need systematic decisions in production, not another research deck.
Build systematic models
Optimize trading and treasury flows
Deploy production infrastructure
Monitor live decisions
What Mnemex builds
A research and deployment layer for systematic digital asset decisions.
Mnemex turns systematic research into reviewable strategy modules, execution logic, treasury analytics, and operational decision engines.
Evidence packages before production decisions.
Backtests, transaction-cost analysis, shadow-mode pilots, drawdowns, turnover, and capacity framing.
Model logic structured for external use.
Signals, routing logic, forecasting models, managed accounts, fixed licenses, and aligned commercial terms.
Infrastructure that supports live deployment.
Risk controls, monitoring, execution assumptions, treasury workflows, and ongoing model review.
Product stack
Strategy models, treasury optimization, and mandate-specific infrastructure.
AlphaShelf. A catalogue of deployable digital asset models.
The primary Mnemex product for investors who want reviewable, outcome-driven strategy modules without building a full internal quant stack.
- Use case
- Strategy selection for portfolio objectives such as protection, diversification, trend participation, and yield enhancement.
- Access
- Review model packages and license the modules that fit the mandate.
Execution and treasury optimization for digital asset flow.
For firms pricing client orders across crypto, stablecoins and fiat, Mnemex builds systematic logic for quote construction, liquidity routing, inventory management and hedge timing.
- Use case
- Improve realised spread, reduce execution leakage, manage residual exposure and measure performance from quote to settlement.
- Access
- Diagnostic, shadow-mode pilot, implementation roadmap and optional production support.
Mandate-specific research and model development.
- Use case
- Designing strategy, signal, execution or treasury logic around a specific universe, exchange setup, exposure target, or risk constraint.
- Access
- Research engagement, signal delivery, implementation support, or dedicated deployment infrastructure.
Operating model
From hypothesis to deployable model or measurable treasury improvement.
The workflow is built to make strategy and operating decisions understandable before capital, engineering time, or production workflow changes are committed.
Define the portfolio or treasury problem, market universe, constraints, and decision criteria.
Evaluate signal logic, transaction economics, robustness, regime behavior, and implementation assumptions.
Package model outputs, decision logic, risk controls, monitoring, and commercial access terms.
Strategy thesisSignal definitionUniverse selectionRisk profile
Drawdown behaviorTransaction-cost analyticsCapacity estimateExecution assumptions
Start a review
Discuss the model or treasury layer your mandate needs.
For institutions, fintechs, brokers, payment businesses and systematic investors evaluating digital asset strategy IP, signal access, execution logic, treasury optimization or deployment infrastructure.