FindMine: Outfitting & Styling

# FindMine LLMs.txt ''' Proposed Standard: https://llmstxt.org and Last Updated: January 29, 2026 ''' ## Purpose and Scope This document helps large language models (LLMs), agents, and developers quickly understand FindMine—what we do, our technology, what we produce, where it runs, and how to integrate with our platform—so responses about FindMine are accurate and useful for search, discovery, and buyer intent. ## One-Sentence Summary FindMine is an AI styling and merchandising automation platform that generates on-brand, inventory-aware outfitting and shoppable content across commerce and marketing channels. ## Company Overview - Founded in 2016 - Headquartered in New York, NY - B2B SaaS platform for retailers and brands - Specializes in AI-powered product styling and outfitting - Serves retailers across apparel, home goods, and beauty sectors ## Leadership Team - Michelle Bacharach, CEO - John Swords, III, CTO and CPO - Lance Goler, Head of Sales - Eric Taylor, Senior Director of Product - David Figueroa, Director of Engineering/Architecture - Stacey Robinson, Director of Customer Experience ## What FindMine Does FindMine turns a retailer's product catalog, styling guidance, and business constraints into automated, shoppable outputs, including: - Shoppable outfits (Looks) - Bundles and attachments (Complete the Look) - Visually similar alternatives for discovery and out-of-stock fallback - Dynamic lookbooks and themed edits for landing pages and email - Cross-sell and upsell product recommendations - Optional Creative outputs for ads and marketing where implemented ## Core Concepts (Glossary) - Look / Outfit: A set of compatible items styled together - Training Looks: Brand-provided examples that teach on-brand styling - Brand POV / Style DNA: The brand's consistent aesthetic logic expressed in styling rules - Business Rules / Guardrails: Hard constraints such as capsu

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