ParastoreTest every retail decision with thousands of AI shoppers before you build.

Parastore

Parastore is an open-source retail simulation platform that uses AI-powered synthetic consumers to test store layouts, product placements, and customer flow strategies without physical risk. Built by Intellicia, it extends LLM-driven virtual personas from digital surveys into 3D physical retail environments, enabling data-informed decisions before committing real-world resources.

Product Highlights

• Synthetic Consumer Simulation: Generate virtual shoppers with distinct personalities, preferences, and behaviors using large language models, then observe how they navigate your store in real-time 3D.
• Visual Store Builder: Design retail spaces with an intuitive isometric grid editor—place shelves, refrigeration units, counters, walls, and entry points while assigning product categories to optimize traffic flow.
• Performance Analytics Dashboard: Track key metrics including visitor count, conversion rates, dwell time, and per-rack engagement through live visualizations that update as the simulation runs.
• Layout A/B Testing: Compare multiple store configurations side-by-side to identify dead zones, optimize circulation patterns, and maximize high-margin product exposure.

Use Cases

• New Store Design & Renovation Planning: Prototype layouts for acquisitions or remodels before investing in physical construction, using simulated foot traffic to validate spatial decisions.
• Product Placement Optimization: Test how repositioning categories or promotional displays affects customer engagement and purchase conversion without disrupting live operations.
• Retail Strategy Education: Serve as a hands-on learning environment for students and professionals exploring consumer behavior, merchandising principles, and spatial design.

Target Audience

Parastore is designed for retail strategists, merchandising professionals, real estate developers, and academic researchers who need to experiment with physical retail concepts. It also appeals to developers and AI researchers interested in agent-based simulations and LLM applications beyond traditional chat interfaces.