Viva Wallet analytics dashboard displayed across multiple monitors
Platform Features

Every tool built for cross-market decision-making

Viva Wallet brings data ingestion, pattern detection, and risk-aware reporting into a single workspace, so you can move from raw market data to a decision without switching tools.

Covering equities, derivatives, and digital assets across major exchanges, with a consistent data model throughout.

A unified data layer for fragmented markets

Investors working across several exchanges and time zones typically stitch together data from spreadsheets, broker terminals, and news feeds. Viva Wallet replaces that patchwork with one structured pipeline that normalizes pricing, volume, and event data as it arrives.

The result is a single source of truth that every downstream feature — screening, forecasting, and reporting — draws from, reducing the reconciliation work analysts usually do by hand.

  • Multi-exchange ingestion

    Feeds from different venues are aligned to a common schema, so instruments are comparable regardless of where they trade.

  • Time-zone normalization

    Session data is timestamped and aligned so activity across regions can be read on one consistent timeline.

  • Structured event tagging

    Earnings, filings, and macro releases are tagged against affected instruments for faster context retrieval.

  • Audit-friendly data trail

    Every processed data point retains its source and timestamp, supporting later review of how a figure was derived.

Models that support judgment, not replace it

Signal confidenceModerate–High
Lookback windowConfigurable
Update frequencyIntraday

Pattern recognition across asset classes

The forecasting engine scans historical and live data for recurring structures — momentum shifts, volatility clusters, correlation breaks — and surfaces them with a confidence indicator rather than a bare prediction, keeping the analyst in control of interpretation.

Risk factors trackedMultiple
Scenario modesAdjustable
Output formatRanges, not points

Risk-adjusted scenario views

Instead of a single forecast line, projections are presented as ranges tied to explicit assumptions. This makes it easier to see how sensitive a view is to a given input before it feeds into a portfolio decision.

Alert typesThreshold, drift, event
DeliveryIn-dashboard
Noise filteringConfigurable sensitivity

Configurable monitoring alerts

Watchlists can be tied to threshold breaches, statistical drift, or tagged events. Sensitivity settings let each user tune how much signal versus noise they want to see, rather than receiving a fixed, one-size-alert stream.

From data to decision in a repeatable flow

STEP 1

Aggregate

Market and reference data from connected exchanges is pulled in, normalized, and stored against a shared instrument model.

STEP 2

Analyze

Screening and forecasting modules run against the aggregated data set, generating ranked views and scenario outputs.

STEP 3

Decide

Findings are laid out in the dashboard alongside the assumptions behind them, ready to inform a position or a review.

How the analysis is built, in plain terms

Viva Wallet is designed around transparency in how figures are produced, so users can judge the reliability of an output rather than accept it on faith.

Documented inputs

Every model output references the data window and parameters used to generate it, viewable alongside the result.

Adjustable assumptions

Key variables in forecasting and risk views can be changed by the user to see how outputs respond, rather than being fixed behind the scenes.

Consistent update cycle

Data refresh and recalculation happen on a defined schedule, so users know how current any given view is at the time they read it.

Viva Wallet workspace showing dashboard configuration and analysis tools

Configured around how analysts actually work

Layouts, watchlists, and alert rules can all be adjusted to match an individual workflow, rather than forcing a fixed structure onto every user. The goal is a dashboard that adapts to the analyst, not the reverse.

Because the underlying data model stays consistent, custom views remain comparable across users and over time, which matters when decisions are reviewed after the fact.

See how the features fit together

Open the dashboard to explore data aggregation, forecasting, and monitoring in one connected workspace.

Explore the Dashboard