PROMETHEUS

Predictive Reasoning and Omnichannel Modelling Engine for Tactical Horizon Evaluation and User Simulation

AI-Powered Customer Digital Twins | Predictive Marketing Intelligence

17 Technologies·8 Key Features·2026·high complexity

Overview

PROMETHEUS is a Customer Futures Intelligence Platform that creates continuously evolving AI Digital Twins for every customer. The platform continuously ingests omnichannel customer interactions and transforms them into living Digital Customer Twins capable of predicting churn risk, purchase intent, customer lifetime value, engagement probability, and campaign outcomes before decisions are executed. PROMETHEUS further extends intelligence through an agent-based simulation engine using Monte Carlo simulation.

Key Features

AI Digital Customer Twins

Continuously evolving models capturing behavior, interests, sentiment, loyalty, engagement, and predicted future actions.

Omnichannel Intelligence

Unifies interactions across websites, CRM, email, support, mobile, and social into a single layer.

Real-Time Event Processing

Kafka-driven event architecture processing interactions continuously.

Predictive Intelligence Engine

Forecasts churn, purchase intent, engagement, sentiment evolution, and lifetime value.

Monte Carlo Campaign Simulation

Digital Twins converted into autonomous agents for probabilistic campaign simulation.

Semantic Customer Memory

Vectorized memories with semantic retrieval using high-dimensional embeddings in Qdrant.

Fatigue-Aware Personalization

Models communication fatigue and channel affinity for optimal engagement.

Executive Intelligence Dashboard

Real-time customer health, churn risk, campaign performance, and predictive metrics.

Technology Stack

Algorithms & Methods

Digital Twin Construction

Customer interactions aggregated into behavior profiles, interest graphs, sentiment trajectories.

Churn Prediction (Ensemble)

LightGBM + XGBoost ensemble identifying at-risk customers.

Purchase Intent Prediction

Transformer-based classification estimating conversion likelihood.

Customer Lifetime Value

Quantile regression with confidence intervals for revenue projection.

HDBSCAN/K-Means Segmentation

Evolving customer cohort identification.

Monte Carlo Simulation

Thousands of probabilistic simulation runs for campaign forecasting.

Semantic Memory (Qdrant)

Vector embeddings for similarity search and contextual memory retrieval.

System Architecture

Event Ingestion Layer

Customer events from CRM, web, email, support, mobile, social

Customer Intelligence Layer

Builds and maintains Digital Customer Twins

Prediction Layer

Churn, intent, LTV, recommendation, segmentation inference

Memory Layer

Vector embeddings and semantic customer memory retrieval

Simulation Layer

Agent creation, Monte Carlo execution, scenario forecasting

Analytics Layer

KPI aggregation, dashboards, reporting, executive intelligence

Results & Outcomes

  • End-to-end AI Customer Digital Twin platform delivered
  • Supports 100,000+ customers and 10M+ events per day
  • Churn prediction, intent forecasting, and LTV estimation integrated
  • Monte Carlo campaign simulation engine operational
  • Transforms CRM from historical records into predictive intelligence
  • Top 10 in TeXpedition hackathon by Epsilon

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