Dynamic Pricing Engine

Part of the worlds-biggest-software-project initiative.

An open-source, AI-native pricing engine that optimises prices in real time based on demand, competition, and inventory.

The Dynamic Pricing Engine is a platform for retailers, marketplaces, and B2B sellers who need to move beyond static rule-based repricing. It combines competitor monitoring, demand forecasting, and reinforcement learning to continuously optimise prices for margin and revenue, while remaining accessible to teams that cannot afford six-figure enterprise contracts.

Why Dynamic Pricing Engine?

Enterprise platforms such as Competera, Pricefx, and Revionics deliver strong demand modelling but are custom-quoted at $50k–$500k+/year and require 3–6 month implementations.
SMB-focused tools like Prisync ($99–$399+/month) are limited to competitor-reactive logic and lack demand forecasting or inventory-aware optimisation.
Mid-market platforms (Omnia, Intelligence Node) sit at $1k–$10k/month but trail Competera in ML depth, and several tools are analytics-focused rather than action-oriented.
The category lacks transparent, open-source tooling that exposes how pricing decisions are made — a gap as the EU Omnibus Directive and GDPR introduce new compliance requirements.
Approximately 48% of enterprise buyers are now actively evaluating AI pricing tools, and 57% of pricing teams are increasing automation budgets, but options remain fragmented between low-end repricers and heavyweight enterprise suites.

Key Features

Competitive Monitoring & Repricing

Competitor price tracking across e-commerce sites and marketplaces
Dynamic repricing engine with automated price updates
Rule-based pricing strategy builder
Real-time price execution with low-latency updates
MAP and MSRP compliance constraints

Demand & Elasticity Modelling

Price elasticity estimation
Time-series demand forecasting integration
Inventory-aware pricing adjustments
Promotional and markdown planning
Profitability and margin analysis

Experimentation & Analytics

A/B testing for pricing strategies
Pricing analytics dashboard
Profit analysis by product, channel, and customer
Historical competitor analysis
Revenue and margin impact simulation

Channel & Platform Integration

E-commerce platform connectors (Shopify, WooCommerce)
Marketplace integration (Amazon, eBay)
Multi-currency and multi-channel pricing
API and webhook support for pricing updates
CSV import/export for bulk pricing operations

AI-Native Advantage

Unlike incumbents that primarily rely on rule-authoring or supervised ML, this project targets reinforcement learning pricing agents that continuously experiment with prices, learn elasticity from outcomes, and self-optimise without manual rule maintenance. Demand forecasting incorporates external signals — weather, events, social sentiment, and macroeconomic data — alongside sales history. Cross-product elasticity modelling captures substitution and complementarity effects to optimise portfolio-level margin rather than isolated SKUs. Natural-language strategy authoring lets merchandisers express pricing intent in plain language ("protect margin on hero SKUs while clearing aged stock") and have the system translate it into executable rules.

Tech Stack & Deployment

The engine is intended to support multi-channel pricing across e-commerce platforms, marketplaces, and POS / inventory systems. Integration targets include Shopify, WooCommerce, Magento, Amazon SP-API, eBay, and data warehouse connectors, with webhook-based price update propagation. Pricing logic is grounded in established price elasticity modelling and revenue management disciplines, with explicit support for MAP/MSRP constraints and EU Omnibus Directive reference-price rules.

Market Context

The global dynamic pricing software market is estimated at USD 3.5–5.0 billion in 2026 and projected to reach USD 6.9–11.9 billion by 2030–2035 at 11–15% CAGR (The Business Research Company, 2026). Incumbent pricing spans $99/month at the SMB end (Prisync) to $50k–$500k+/year for enterprise platforms (Competera, Revionics, Pricefx). Primary buyers are VPs of Pricing or Revenue Management, Directors of E-Commerce, and Category Managers across retail, hospitality, airlines, travel, and marketplace selling.

Project Status

This project is in the research and specification phase.
Contributions, feedback, and domain expertise are welcome.

Contributing

We welcome contributions from developers, domain experts, and potential users. See CONTRIBUTING.md for guidelines.

Important: All contributions must be your own original work or clearly attributed open-source material with a compatible licence. Copyright infringement and licence violations will not be tolerated and will result in immediate removal of the offending contribution. If you are unsure whether a piece of code, text, or other material is safe to contribute, open an issue and ask before submitting.

Licence

Licence to be determined. See discussion for context.