Parastore

What it does

Parastore is an open-source (MIT) retail simulation where LLM-powered synthetic consumers walk through a 3D virtual store, browse shelves, and make purchase decisions. Each consumer follows one of 12 behavioral patterns with grammar-constrained actions, randomized context (mood, budget, company), and impulse-buy logic triggered by what they see along their route. Validated against real POS data with 0.955 Spearman correlation. Python/FastAPI + React/Three.js. Any LLM backend.

Draw a store, generate LLM personas, and watch them shop — an isometric 3D sandbox for synthetic-consumer experiments. - intellicia-public/parastore

Build, simulate, and optimize retail spaces with synthetic consumers. intellicia builds tooling around synthetic consumers — virtual personas generated by LLMs that we run surveys against in place of (or alongside) real respondents. Parastore is an experiment in extending that idea from surveys to physical retail : if we can simulate how a synthetic shopper answers a survey question, can we also simulate how they walk through a store, what they pick up, and what they end up paying for? This repository is a prototype , not a production forecasting tool. A rigorous offline-sales model would need POS history, real foot-traffic data, SKU-level taxonomies, weather/seasonality signals, queueing…from github.com

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