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Milo - Overview
An AI customer service agent, it is built using Retrieval-Augmented Generation (RAG), designed for enterprise-grade customer support and knowledge assistance.
It works on a RAG Architecture, meaning it collects data from sources like websites, documents, FAQs, and product catalogs — into real-time, human-like conversations, while maintaining safety, control, and reliability.
In this project, Distinct Cloud Labs built an enterprise-ready RAG-powered AI chatbot that can be deployed on websites and channels like WhatsApp, Instagram, and other Social Channels
What we built
Built an enterprise-ready, AI Agent deployable across websites and WhatsApp, designed for accurate, secure, and scalable customer interactions.
Knowledge Ingestion Layer
Ingests data from websites, PDFs, internal documents, FAQs, and e-commerce systems
Cleans, chunks, embeds, and stores data in a vector database
Enables precise, context-aware retrieval at query time
AI Chatbot Layer
Understands user intent and performs semantic search over business knowledge
Generates grounded, factual responses using retrieved context
Designed to minimize hallucinations
Supports conversational memory and human escalation
Delivery Layer
Deployable as a website chatbot widget
Available as a WhatsApp AI support agent
Our Tools
Our Development Stack.
Python Fast API
Langchain
Azure
Open AI
Pinecone
Mongo DB
React
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