Add Your Knowledge Base
Sabse pehle, aap apni business ki information Botaura mein add karte hain. Yeh multiple methods se ho sakta hai:
File Upload
PDF, DOCX, TXT aur knowledge documents upload karen.
Website Crawling
Website URL dein aur Botaura automatically pages crawl karega.
Manual FAQs
Custom FAQs aur business responses manually add karen.
AI Embeddings & Vector Processing
Botaura uploaded content ko intelligent chunks mein divide karta hai aur semantic embeddings create karta hai.
What are Embeddings?
Embeddings mathematical representations hoti hain jo text ka meaning samajhti hain — exact keywords ke bina bhi relevant answers find karne mein help karti hain.
Hum all-MiniLM-L6-v2 embeddings model use karte hain with PostgreSQL + pgvector for blazing fast semantic retrieval.
Customize Your AI Chatbot
Apni chatbot ko fully brand-matched experience mein convert karen.
Embed Anywhere
Ek simple script snippet ke through chatbot ko kisi bhi website par install kar sakte hain.
<script
src="https://botaura.com/widget.js"
data-business-id="your-id">
</script>WordPress, Shopify, Wix, custom websites — sab platforms supported.
RAG-Powered AI Conversations
Customer message aate hi Botaura ka Retrieval-Augmented Generation system activate hota hai.
Question analysis & embedding generation
Semantic vector similarity search
Top relevant knowledge retrieval
Context-aware LLM response generation
Confidence scoring & fallback handling
Lead Capture & Analytics
Botaura conversations ko business opportunities mein convert karta hai.
Technology Behind Botaura
AI Models
Database
Infrastructure
Security
Common Questions About Botaura
What is RAG technology in AI chatbots?
RAG (Retrieval-Augmented Generation) is an AI architecture that combines semantic search with large language models. It retrieves relevant information from your knowledge base using vector embeddings, then generates contextually accurate responses. This ensures chatbot answers are grounded in your actual business data.
How does Botaura process my business knowledge?
Botaura converts your uploaded documents, website content, and FAQs into semantic embeddings using the all-MiniLM-L6-v2 model. These embeddings are stored in a PostgreSQL database with pgvector extension, enabling fast similarity search when customers ask questions.
What languages does Botaura support?
Botaura natively supports English, Urdu, and Hinglish (Roman Urdu). The AI understands questions in any of these languages and responds appropriately, making it perfect for businesses serving multilingual customers in Pakistan and South Asia.
How long does it take to set up a Botaura chatbot?
Setup takes less than 5 minutes. Upload your knowledge base files or provide your website URL, customize the chatbot appearance and personality, then embed a simple script on your website. The AI processes your content automatically and is ready to answer questions immediately.
What is semantic search and why is it better than keyword matching?
Semantic search understands the meaning and intent behind questions, not just keywords. If a customer asks "delivery time to Lahore" and your content says "shipping duration to Lahore is 2 days", semantic search connects these concepts even without exact word matches, providing more accurate answers.
Ready to Build Your AI Chatbot?
Setup takes less than 5 minutes. Upload your business knowledge and launch your AI support assistant instantly.