Network Intelligence
AI that runs on deterministic data.
Network Intelligence is the AI processing layer that transforms DataBillity's consented data lake and cross-network signals into actionable business outcomes - recommendations, predictions, next-best-actions, and autonomous agent decisions.
Why it matters
Most enterprise AI fails for one reason: the data.
Enterprise AI projects don't fail because the models are wrong. They fail because the data is wrong - scraped, stale, probabilistic, ungoverned, or all four.
Typical enterprise AI
- Third-party data purchased quarterly
- Probabilistic identity matching
- Cookie-based behavioral signals (deprecated)
- Siloed training data from one business
- Compliance bolted on after model training
- 6-12 month implementation timelines
DataBillity Network Intelligence
- Consented first-party data, refreshed in real time
- Deterministic identity resolution (verified IDs)
- Cross-network behavioral signals (consent-governed)
- Multi-business training corpus (network effect)
- Consent-coupled at the model input layer
- Pre-trained models with 90-day deployment path
The AI stack
Four models. One ensemble. Zero guessing.
Network Intelligence is an ensemble of four specialized architectures combined through a learned weighted ranking system that produces a single, explainable output.
1. Collaborative Filtering (ALS)
Identifies what similar customers have done across the network to surface opportunities the individual business would never see.
Strength: Cold-start mitigation · Cadence: Nightly retrain + hourly incremental
2. Sequential Recommendation (SASRec)
Self-Attentive Sequential Recommendation model that learns from the ORDER in which customers act - not just what they do.
Strength: Temporal pattern recognition · Cadence: Weekly retrain
3. Large Language Model reasoning
Generates recommendation rationale, campaign copy, and SMS content. The LLMs receive anonymized behavioral profiles and context.
Strength: Explainability, content generation · Cadence: Real-time inference
4. Graph Neural Network (GNN)
Ensemble on a heterogeneous customer-product-tenant-mobility graph. Cross-tenant edges are consent-gated for privacy preservation.
Strength: Network-wide pattern discovery · Cadence: Weekly full retrain
Ranking & consent
Ranked by AI. Filtered by consent.
The four models produce candidate recommendations independently. Then the consent engine runs: every recommendation is filtered against the consumer's active consent scope.
Privacy guardrails
CCPA/CPRA, TCPA, CASL, and GDPR guardrails are enforced at output time - as a hard constraint in the ranking function.
Explainability
Every recommendation includes an LLM-generated rationale explaining WHY it was surfaced. No black boxes.
Feedback loop
Click, purchase, and dismiss outcomes feed back into the ensemble weights via online learning. The system gets smarter with every interaction.
Delivery
Intelligence delivered everywhere.
Chat widget
Sub-100ms P95 delivery of personalized recommendations via the Billity AI chat widget.
SMS channel
TCPA-gated, consent-verified SMS delivery. Personalized copy generated by the LLM layer.
Team dashboard
Ranked recommendation lists, next-best-action cards, and LLM-generated explanations for sales reps.
Ad platform export
Hashed segment export to Meta, Google, and The Trade Desk. Requires ad_targeting consent scope.
API access
Full programmatic access to Network Intelligence outputs via the API Platform.
Custom integrations
Webhook-driven delivery to CRM, DMS, marketing automation, and analytics platforms.
Intelligence that compounds. Privacy that doesn't compromise.
See how Network Intelligence turns consented data into autonomous business outcomes.