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DEVELOPMENT PLAN

1. Product Strategy and Definition

Goal

Build a Shopify extension that:

• Loads all Shopify store products
• Extracts structured product data
• Feeds product data + external knowledge sources into a RAG backend
• Answers customer questions via conversational AI in real time

Target users

• Shopify stores of all sizes
• Stores with >100 products who want better AI assistance
• Merchants looking for AI to reduce support costs and increase conversions

Value propositions

• Instant AI answers based on actual store catalog
• Supports multilingual catalogs
• Smart fallback to external knowledge (brand FAQs, shipping policies, etc.)

Deliverables:

• Core Shopify extension
• Backend system with product ingest + RAG pipeline
• Web admin dashboard for settings and analytics
• Chat widget for storefront

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2. Technical Architecture

Front end

• Shopify App Extension (Theme App Extension)
• Embedded App via Shopify App Bridge
• Storefront Chat UI built with React

Backend

• Node.js / Python (FastAPI) microservices
• Database (PostgreSQL / MongoDB) for storing products and knowledge base
• Search Engine (Elasticsearch, Pinecone, or Weaviate)

AI / RAG

• Ingest product data into vector store
• Use OpenAI embeddings
• Prompt engineering for RAG queries
• Caching layer for repeated questions

Shopify Integration

• Admin API for product fetch and updates
• Webhooks for real-time product sync
• ScriptTag or Shopify UI Extension for Customer Chat

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3. Product Development Roadmap

Phase 0 - Research & Scoping (Week 1)

• Identify data fields needed for product understanding
• Study Shopify Docs for extensions and API limits
• Evaluate vector DB (Pinecone vs Milvus vs Weaviate)
• Set AWS / GCP / Azure infra

Phase 1 - MVP Backend & Data Ingestion

• Create app skeleton with Shopify CLI
• Build product sync module
  • Full catalog import
  • Delta updates with webhooks
• Define knowledge base schema
• Setup vector DB + embeddings pipeline

Phase 2 - AI & RAG System

• Write embedding generators
• Build RAG prompt templates
• Test quality with sample products
• Implement fallback sources (FAQs, policy docs)

Phase 3 - Chat UI & Shopify Extension

• Build storefront chat widget
• Integrate chat with backend
• Add admin UI for settings (chat styles, triggers)

Phase 4 - Analytics & Learning

• Track user queries
• Improve prompts based on usage
• Dashboard for merchants (top questions, metrics)

Phase 5 - QA and Pre-Launch

• Store testing
• Cross browser/device testing
• Secure OAuth and OAuth scopes
• Beta release to test merchants

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4. Key Technical Considerations

Product Ingestion

• Sync all product attributes
• Use Shopify webhooks to maintain updates
• Normalize variants and metafields

Vector Storage

• Use a scalable store
• Incremental updates without full reingest

Prompt Engineering

• Mix product data + store policies
• Reuse OpenAI search / embeddings
• Example:

System: You are a Shopify product support AI
Context: [Product description, price, tags]
Question: [User query]

Latency

• Pre-cache common questions
• Fast retrieval from vector DB

Security

• Store tokens securely
• Respect store privacy

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Docs & Competitors

Setup Shopify & App

Design database schema for RAG

Marketing Plan