Profile-of-One
AI-Powered Personalization
for Personalized Decision Intelligence

Build . . .

a rich understanding of all entities including your customers and products

Select . . .

the right intervention (e.g., personalized action) for the right actor at the right time via the right channel with evidence

Learn . . .

which interventions are driving the best outcomes, the most engagement, higher conversion rates, and more

Measure . . .

the impact of interventions on key performance indicators (revenue, costs, productivity, satisfaction)

Assure . . .

integrity and trust around data privacy, model confidence, regulatory compliance to CCPA, GDPR, local regs (Learn more about Trust & Governance)

Classification

Predict entities belonging to categories. Example: Call likelihood for an insurance claim.

Similarity

Find similarities between entities. Example: Finding similar profit centers for a commercial customer.

Segmentation

Identifying and grouping similar entities. Example: Members that are prone to being delinquent on a loan or medical bill.

Forecasting & Simulation

Simulate “what if” scenarios using synthetic data. Example: Time series forecasting of new admissions for Covid-19 patients.

Feature Store

Use Profile-of-One to power different ML model training and inferences. Example: Classification model for fraud, waste and abuse in medical claims.

Temporal Analysis

Query for changes to a profile over time. Example: How customer behavior or characteristics changed over time.

Personalized Insights

Get insights and evidence based on learnings about a customer. Example: Detect agent fraud based on prior transactions and policy enrollments.