House of Cookies

Conversational AI, Retail Support & RAG Systems

SCALE

2M+

Daily Requests

UPTIME

99.9%

System Availability

ACCURACY

+20%

With Multimodal Input

PIPELINE

RAG

Airflow Orchestrated

FALLBACK

AWS

Bedrock LLM Routing

Background

Where customer volume breaks the human chain

Scaling support to millions of users often leads to fragmented context and inconsistent service quality. Human-only teams can no longer maintain accuracy or speed under the weight of repetitive inquiries.

The Intellema Design Challenge

Retail and service brands frequently struggle with high volumes of customer questions spanning pricing, locations, and orders while preserving accuracy and consistent tone. These surges create bottlenecks that overwhelm manual support chains, leading to delayed resolutions and a breakdown in user trust.

This project delivers an AI-powered RAG chatbot capable of handling over 2 million daily requests and interpreting informal, multilingual text. The architecture ensures dependable runtime behavior and high availability even during extreme peak traffic surges.