Vaultmere Custody aggregates positions across multiple exchanges through API-led aggregation and applies latent pattern recognition to flag risk and surface rebalancing opportunities, without taking custody of your funds.
Visualization of volatility and liquidity signals aggregated across connected accounts, updated as new data arrives.
Most analytics tooling is designed for institutions with dedicated risk teams. Vaultmere Custody is scoped for a single operator who needs clear, defensible information without a research department behind them.
The platform reads account and market data through exchange APIs, consolidates it in one place, and applies statistical models to describe what is happening to capital that is currently idle between client engagements. It does not place trades on your behalf and does not require withdrawal permissions on any connected account.
Freelancers typically hold balances across two or more exchanges, often opened for different reasons at different times. Vaultmere Custody connects to each account through read-only API keys and reconciles balances, open positions, and historical transfers into a single ledger view.
The result is a consolidated picture of exposure that would otherwise require manually cross-referencing several platforms. Position sizing, correlation between holdings, and idle cash are shown together, so decisions are made against the full picture rather than a fragment of it.
Between projects, capital that would normally be reinvested into work often sits exposed to market movement with no one actively watching it. The engine is built to narrow that gap.
Historical volatility and correlation across connected assets are modeled continuously. When exposure concentration crosses a defined threshold, the dashboard surfaces it directly, rather than requiring a manual review.
Data refreshes on a rolling basis as exchanges publish updates. Price, liquidity, and position changes are reflected in the unified view without requiring a manual refresh across each individual platform.
Recommendations are presented as structured options with the underlying reasoning shown, not as a single automated action. You retain full authority over what gets executed and when.
The process is split into three stages so each one can be audited independently, which matters for a technical user deciding whether to connect financial data.
Read-only API keys pull balance, position, and transaction history from each connected exchange on a scheduled interval. No withdrawal or trading permissions are requested at this stage.
Ingested data is normalized into a common schema and passed through statistical models that assess volatility, correlation, and concentration across the full set of holdings.
Findings are translated into a ranked set of options, such as rebalancing suggestions or liquidity adjustments, presented with the data points that support each one.
A freelancer closes a project and holds the proceeds in stablecoin or fiat-pegged balances while sourcing the next contract. The dashboard tracks how that reserve is distributed across exchanges and flags when a single platform holds a disproportionate share of it.
When a gap between contracts extends beyond a few weeks, part of the reserve may be positioned for longer-term growth. The analysis layer monitors how that allocation behaves relative to the liquid portion, so a correction in one does not go unnoticed by the other.
Leave a work email and we will send setup instructions for read-only API connections, along with the current documentation for the analysis engine.
Typical onboarding, from first API connection to a populated dashboard, takes under 15 minutes.