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Turn every signal into decision-ready intelligence
Bring streaming, batch, first-party, and third-party data into one real-time intelligence layer. DataVisor normalizes, enriches, and transforms raw events into features that rules, machine learning, graph intelligence, and decisioning can use immediately.
Put every relevant signal to work
Unify transaction, account, identity, device, behavioral, network, historical, and third-party data so every decision starts with richer context.
Put every relevant signal to work
Unify transaction, account, identity, device, behavioral, network, historical, and third-party data so every decision starts with richer context.
Create features at the speed of the event
Calculate velocity, behavioral, historical, and relationship features as activity happens, then make them immediately available across detection and decisioning.
Add external intelligence before the decision
Orchestrate identity, device, KYC, risk, and other enrichment sources within the decision flow so teams can use the signals they trust without stitching together separate pipelines.
From raw event to decision-ready context
An incoming event is validated, the entity is enriched, real-time features are computed, and the resulting intelligence becomes available to rules, models, graph analysis, and decisioning — all before the transaction completes.
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One intelligence path from data to action
Ingest activity from any supported source.
Normalize and enrich the incoming data.
Compute real-time and historical features.
Make intelligence available to rules, ML, graph, and decisioning.
Capture outcomes to strengthen future strategies.
Keep data, features, and decisions in the same operating loop
DataVisor connects data orchestration directly to the detection and decisioning layer. Teams can introduce new signals and features without rebuilding a fragmented set of pipelines for every model, rule, or workflow.
One data foundation across the fraud lifecycle
Power account opening, account takeover, card and payment fraud, ACH and wire monitoring, scams, mule detection, and investigations with the context each use case requires.
Built for high-volume, low-latency environments
New data providers can typically be onboarded in as little as two days, so strategies stay current as your data footprint grows.
The intelligence layer beneath every decision
Real-Time Data Orchestration feeds Real-Time Decisioning, Rules & Features, Supervised and Unsupervised ML, Knowledge Graph, dEdge, and Analytics with a common stream of decision-ready context.
Keep the data path governed and resilient
Support schema evolution, data-quality controls, lineage, access controls, and resilient handling of unavailable enrichment sources so production strategies remain dependable as data changes.
- Schema evolution without pipeline rework
- Data-quality controls and validation at ingest
- End-to-end data lineage
- Role-based access controls
- Graceful handling when enrichment sources are unavailable
Common questions
Can DataVisor combine streaming and batch data?
Yes. DataVisor can use live event data alongside historical and batch context so strategies can evaluate what is happening now against what happened before.
Can we use our existing third-party data providers?
DataVisor is designed to incorporate external identity, risk, and enrichment signals through integrations and APIs, allowing teams to preserve the data sources that already add value.
Make more of every signal
See how DataVisor turns fragmented data into real-time intelligence that can be used across fraud detection, decisioning, and investigations.