AI ConsultingLLM · Fashion2024

Styllica

LLM RAG commerce assistant for fashion brands.

RAGCommerce AI

Challenge

In online fashion brands, the customer journey began with a poor filtering experience and ended with high cart abandonment rates. Personalized product advisory was creating an unscalable customer service burden.

Approach

An LLM RAG pipeline built on AWS Bedrock created a chatbot system that knows the product catalog and makes recommendations based on customer preferences. Docker and an AWS service stack (EC2, ECS, S3, RDS) were used for high availability and auto-scaling.

Technologies

Python
AWS Bedrock
LLM RAG
Docker
AWS EC2
AWS ECS
AWS S3
AWS RDS
FastAPI

Outcome

RAGCommerce AI

RAG pipeline and AWS infrastructure for a chatbot that helps online fashion brands shorten shopping time.

Next step

Build the next AI capability your company can actually use.

A focused intro call is enough to clarify the track, scope, and next practical step.

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