Asset, currency, size, direction, urgency, client segment and settlement constraints.
Treasury and execution optimization
Optimise quote construction, routing and hedging.
Mnemex builds the models and execution systems required to price client order flow, select liquidity, manage inventory, and hedge exposure across venues. Lower slippage. Better spread capture. Tighter risk control.
Built for businesses handling recurring client orders across crypto assets, stablecoins, exchanges, liquidity providers, bank rails and settlement currencies.
Pricing model expected hedge and execution cost
Routing score providers by executable outcome
Risk manage inventory and residual exposure
Execution intelligence layer
Customer orders routed through systematic decision logic
Expected execution cost, fill probability, adverse selection, inventory impact and hedge urgency.
Offsetting orders, target inventory, net exposure, passive execution and residual-risk limits.
Exchanges, OTC desks, LPs, stablecoin rails, banking cut-offs, fees and transfer costs.
TCA, rejected fills, slippage, spread capture, hedge PnL, limit breaches and settlement exceptions.
Client order flow is an operating asset
Realised economics depend on what happens after the quote.
Payment, brokerage and liquidity businesses often treat every order as an isolated hedge. A more institutional approach manages orders as a stream of digital asset flow: net what can be internalised, route what must be externalised, and measure the full economics after settlement.
Operating pressure
Execution quality is decided before the hedge.
Taker costs and market impact
External hedge turnover
Inventory and settlement drag
Immediate hedging
Hedging every ticket externally increases fees, spread cost and market impact.
Headline-price routing
The best displayed price can be poor after depth, rejects, latency, fees and settlement cost.
Static inventory
Arbitrary balances create funding drag, avoidable transfers and missed internalisation opportunities.
Reactive liquidity
Liquidity is sourced after the order arrives instead of being forecast and pre-positioned.
Weak attribution
Without decision-to-settlement TCA, pricing, routing and treasury decisions remain hard to govern.
Electronic market expertise
Execution discipline from HFT, market making and FX liquidity.
Mnemex applies the operating logic used in electronic markets to digital asset order flow: price expected risk, anticipate liquidity needs, route by executable outcome, internalise where possible and hedge only what remains.
The benefit is practical: less avoidable spread cost, fewer unnecessary external hedges, better use of inventory and clearer attribution of realised economics.
Reduce taker costs and market impact.
Capture more value from offsetting client orders.
Improve routing decisions when liquidity conditions change.
Position inventory before predictable demand arrives.
Give treasury and trading one measurable decision framework.
Execution intelligence platform
A model layer for pricing, routing, internalisation, inventory and risk.
The platform sits between customer orders and external liquidity. It scores expected execution outcomes before a decision is made, then measures realised economics after settlement.
Net offsetting client orders before trading externally.
Reduce external turnover by matching compatible flow, using inventory intelligently and hedging only residual exposure.
Route by expected executable cost, not headline quote.
Score LPs, exchanges and OTC desks using price, depth, fees, latency, rejection probability, limits and settlement terms.
Position liquidity before predictable demand arrives.
Use seasonality, merchant patterns, market conditions and client segmentation to forecast direction, size and urgency.
Manage balances as a constrained optimisation problem.
Set target balances, rebalance timing, exchange allocation, funding source and liquidity buffers under operational constraints.
Predict provider behaviour across market regimes.
Estimate fill probability, rejection risk, expected slippage and capacity before allocating flow to each venue or contributor.
Close the loop from decision to settlement.
Attribute realised spread, hedge cost, slippage, exceptions and residual exposure to the decisions that created them.
Stage-gated engagement
Validate the execution logic before changing production decisions.
The engagement is designed to reconstruct current realised economics, build a shadow decision engine, and test whether new logic improves outcomes before it touches production.
Reconstruct quote-to-settlement economics, LP behaviour, hedge cost, inventory usage and settlement constraints.
Run pricing, routing, internalisation, inventory and hedge decisions against historical and live read-only data.
Quantify uplift, define risk limits, document integration requirements and specify fallback logic.
Order-flow reconstructionTransaction-cost analyticsProvider scorecardsShadow decision engine
Flow forecastsInventory policyHedge thresholdsSettlement constraints
Limit frameworkFallback logicException controlsProduction specification
Measurement framework
Measure decisions like an electronic execution desk.
Success is measured from quote request through execution, hedge and settlement. The objective is improved realised economics without weakening fill quality, reliability, limits or operational control.
Quoted spread, realised spread, fees, market impact, transfer cost and leakage.
Fill and reject rates, slippage, latency, stale quotes, venue capacity and price improvement.
Internalised volume, external hedge turnover, inventory utilisation and rebalancing frequency.
Directional accuracy, calibration, flow-size error and stability across market regimes.
Unhedged duration, residual inventory, drawdown of hedge PnL, limit breaches and overrides.
Decision logs, contributor reviews, model monitoring, exception reporting and escalation thresholds.
Controls first
Systematic decisions without giving up desk control.
Mnemex can work from anonymised, read-only order, quote, fill, hedge, inventory and settlement data. Production use remains subject to approval, limits, fallback logic and human oversight.
The engagement can analyse and recommend without moving funds or executing trades.
Pricing, routing, internalisation, inventory and hedging decisions are evaluated against real data first.
Steering reviews focus on realised economics, control breaches, model behaviour and implementation constraints.
Implementation specifications include limits, audit logs, fallback behaviour, monitoring and exception handling.
Start with one corridor
Start with one asset, corridor or liquidity path.
A practical first step is a working session with treasury, trading, product and engineering, followed by a limited anonymised data sample. Mnemex can return a baseline execution diagnostic, value-pool hypothesis and shadow-engine pilot scope.