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Platform · Decide — Intent

Intent.
Decide in milliseconds.

Real-time decisioning over every signal — propensity, next-best-action, churn, fraud, eligibility and explainable AI, all running inside your perimeter with a full audit log.

Talk to Solutions See Allyvate AI →
Decisioning Console
LIVE
Models in production
Propensity
XGBoost
NBA / NBO
Bandit
Churn
Survival
Fraud
Iso·Forest
LTV
Pareto/NBD
Eligibility
Rules+ML
Recommend
Two-tower
Risk Score
GBM
Decisioning trace · live
PROPENSITY
Term deposit · score 0.87
12ms
NBA
Offer A > Offer B (Δ +18%)
9ms
CHURN
Risk 0.72 · 30-day window
7ms
FRAUD
Anomaly 0.94 · block
5ms
GUARDRAIL
Consent + region check passed
2ms
8 models live 3.2M decisions / hr P95 14ms
What is Intent

Decisioning that fires the moment a signal arrives.

Intent is the Decide layer of the Appice loop. Every signal from Integrate is scored, ranked and gated — through models, rules and regulatory guardrails — before anything reaches a customer. Decisions land in milliseconds, with reason codes attached.

Sub-15ms decisions

Models and rules co-execute in-stream — no queue, no batch scoring window, no waiting for a nightly run.

Explainable by design

Every decision carries reason codes, feature contributions and a full audit trail — ready for regulators and risk committees.

Guardrails-first

Consent, residency, eligibility and frequency limits are checked before any decision is acted on.

Model Catalogue

Every predictive model Intent runs.

Out-of-the-box model families — pre-trained on industry-specific signals and retrainable on your own data. Bring your own models too: BYO MLflow, SageMaker, Vertex AI or custom binaries.

Propensity Models
Product propensity (cross-sell)
Upgrade / upsell scoring
Conversion likelihood
Channel response propensity
Offer acceptance prediction
Next Best Action
NBA ranking engine
Multi-armed bandit experiments
Reinforcement-learning agents
Offer eligibility scoring
Channel arbitration
Churn & Retention
Churn risk (30/60/90-day)
Account-dormancy prediction
Wallet-share decay
Renewal / win-back likelihood
Subscription decay
Fraud & Risk
Real-time anomaly detection
Transaction-pattern scoring
Account-takeover signals
Velocity / device-graph rules
AML alerting hooks
Customer Lifetime Value
Predicted CLV
Revenue-trajectory modelling
Profitability tiering
Cost-to-serve prediction
Margin-aware ranking
Segmentation & Scoring
Behavioural segmentation
RFM / engagement scoring
Look-alike audiences
Micro-segment generation
Dynamic cohort assignment
Eligibility & Rules
Visual rules engine
Regulatory guardrails
Consent / opt-in checks
Frequency & fatigue caps
Region / residency rules
Explainable AI
Per-decision reason codes
Feature-contribution traces
Model-version pinning
Bias & drift monitoring
Full audit log export
Bring Your Own Models
MLflow registry
AWS SageMaker endpoints
GCP Vertex AI
Azure ML
Custom Python / ONNX binaries

See how Allyvate AI orchestrates these models →

How Intent fits in the loop

Sense → Decide → Act → Learn.

Intent sits between Integrate and Interact — every signal becomes a scored, audited decision before it ever turns into a message, action or block.

01

Signal arrives

A typed event from Integrate — transaction, behaviour or anomaly.

02

Models score

Propensity, churn, fraud and CLV models execute in parallel — milliseconds end-to-end.

03

Rules & guardrails

Consent, eligibility, frequency and regional checks gate the decision.

04

Hand-off to Act

Interact executes — message, offer, block, escalate — with reason codes attached.

Ready to decide

See Intent score your data.

Send us a sample event flow — we will show you the models that fire, the reason codes they emit, and the actions they would trigger.

Book a Working Session See Allyvate AI →