AI Decision Engine

What's Inside

BIGDBM's AI Decision Engine sits on top of the identity graph — ingesting consumer, B2B, property, healthcare, and sports data to produce audiences, scored appends, and automated decision layers. The more signals fed in, the smarter the output.

Audience Creation

Build precise consumer and B2B audiences using AI-scored attributes and signals.

Intelligence Append

Enrich any file with AI-prioritized consumer, B2B, and property fields before delivery.

Healthcare

AI-driven segmentation across patients, caregivers, and healthcare professionals.

Sports

Fan and collector audience modeling powered by behavioral and affinity signals.

Engineered for Trust

Model-Driven

Machine learning models trained on billions of identity signals continuously refine audience quality and append accuracy.

Signal-Scored

Every output is ranked by confidence — recency, frequency, intensity, and strength — so decisions are based on the best available signal, not just the most recent one.

Privacy-Compliant

All AI outputs are derived from consent-managed, CCPA-compliant data sources with opt-out processing built into every model run.

Continuously Improving

Models are retrained as new data flows in — weekly and monthly — so every audience and append gets sharper with each cycle.

Data Inputs

Signals

Behaviour

Intent

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Data Marketplace

AI Models

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Audiences

Decision Output

How Teams Get Results

Marketing & Growth

Build lookalike audiences from your highest-converting customers using AI-scored attributes.
Suppress non-reachable contacts automatically before a campaign goes out.
Identify and prioritize in-market consumers using real-time intent signals fed into the model.

Analytics & Data Science

Train propensity and churn models using AI-appended behavioral and demographic fields.
Validate and improve internal model performance with confidence-scored external signals.
Attribute campaign outcomes back to the signals that predicted conversion.

Risk, Compliance, and Ops

Use AI-scored identity fields to flag low-confidence records before they enter a workflow.
Automate decisioning on contact quality for account approvals or fraud screening.
Maintain compliance by running decisions only on data with verified consent lineage.

FAQ

What data sources power the AI Decision Engine?

The engine draws from BIGDBM's full identity graph — consumer, B2B, property, healthcare, and sports datasets — all multi-sourced, scored, and refreshed on weekly and monthly cycles.

How is the AI different from a standard data append?

A standard append adds fields. The AI Decision Engine scores every field by confidence using recency, frequency, intensity, and strength signals, then ranks outputs so downstream decisions are based on the best available signal, not just the most recent one.

Can I use the AI Decision Engine on my own first-party data?

Yes. You can feed your first-party data into the engine and receive AI-scored appends and audiences back, enriched against BIGDBM's identity graph.

How often are the models retrained?

Models are retrained on weekly and monthly cycles as new data flows in, so every audience and append gets sharper over time.

Is the AI Decision Engine available for healthcare use cases?

Yes. The engine supports AI-driven segmentation across patients, caregivers, and healthcare professionals using compliant healthcare data inputs.

What verticals does the AI Decision Engine support?

The AI Decision Engine supports consumer, B2B, property, healthcare, and sports verticals, with purpose-built audience models and scored appends for each.