This page aims to explain the main differences between PO.AI Optimization Engine and classic Machine Learning modelling machine learning modeling and how PO.AI Optimization Engine interacts with other Pricefx modules.

Advantages

PriceOptimizer^AIOptimization Engine, once fully configured, combines powerful, transparent segmentation and guidance with AI-based multi-constraint full-price waterfall optimization.

Machine Learning Segmentation and Predictive modeling	MAAI-based Optimization Engine Full Price Waterfall Optimization
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Data-driven or rules-based / Predefined, managerial segmentation model Calculation of optimized deal guidance based on: Margin or discount based distribution (B2B) Price elasticity (B2C) Identification of Cross-Sell and Upsell opportunities ℹ

Machine

Learning

learning is not part of the demo solution out-of-the-box.

Multi-Agent

ArtificiaI

Artificial Intelligence (MAAI) powered engine to simultaneously optimize any price waterfall element at any level of granularity  Glass box and interpretable AI Considering multiple constraints and business strategies Understanding interactions and indicating which constraints

are impacting

impact the optimization results Simulating results

Background

PriceOptimizer^AI Optimization Engine module is built around Optimization Engine backend which is a Multi-Agent System to optimize prices, discounts, or any continuous values with respect to for any user-defined criteria, such as margin targets, revenue targets, and custom business rules. Optimization Engine backend is basically a giant computation graph representing all the variables, computations, and criteria in the problem and their relationships. Each node of the computation graph is an autonomous agent. At runtime, agents cooperate with each other to gradually converge towards the values that satisfy all the criteria, or towards the best compromise in case of conflicting criteria (such as increasing margin but also keeping prices as stable as possible).

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Position within Pricefx Platform

The following diagram focuses on PriceOptimizer^AI position within our Optimization Engine position within the Pricefx cloud-native 360° pricing platform:

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Accelerator and Setup

The current PO.AI Accelerator To get started, the easiest way is to use an optimization accelerator using the Optimization Engine (see Optimization Engine). It deploys a set of Logics logics to tackle a “Waterfall Optimization” problem as described in PO.AI Accelerator Overview.In order to set up PO.AIgiven optimization problem.

To set up Optimization Engine, you need to first understand the customer’s domain and requirements, and turn them into a 'problem description' that is fed to the Optimization Engine backend. Each instance of PO.AI Optimization Engine has its own specific problem description file which is the result of problem modeling. It can be configured based on PO.AI Accelerator, documented in POAI Accelerator: an accelerator for PO.AI modulePrice Waterfall Optimization Accelerator; for details see Customize Optimization.