Hero
Generative & Agentic AI
RAG & Knowledge Systems
Home Improvement Retail

RAG-Powered Project Guidance Assistant for a Home-Improvement Retailer


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Problem

Project know-how scattered everywhere

A 26-store home-improvement retailer had product documentation, installation guides, how-to articles and supplier spec sheets scattered across a PIM, a legacy CMS, thousands of PDFs and staff memory. Shoppers asking what they needed to tile a bathroom got a different answer in every store, and the website's search returned products — never guidance on how to use them.

Solution

Retrieval-grounded guidance assistant

We built a retrieval-augmented guidance assistant over a unified index of roughly 40,000 documents spanning product specs, installation guides and buying advice. Shoppers describe a project in plain language and receive a step-by-step plan with the exact products, quantities and tools required, every answer citing its source documents. Store associates use the same assistant on handheld devices in the aisles.

Measurable Impact

What changed after launch

Project-guidance sessions converted to purchase at 2.4x the rate of standard site search

Average basket on assistant-led orders 31% larger than the storewide online average

Associate product-question escalations to head office reduced by 57%

93% of sampled answers cited a verifiable source document in monthly accuracy audits

Tech & Tools Used

What powered the build

Python (FastAPI)
LangChain
OpenAI API
pgvector
PostgreSQL
Elasticsearch
Next.js
Redis
AWS S3 + ECS

Ready to Build your Home Improvement Retail Business with RAG & Knowledge Systems

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