Add Your Knowledge Base
First, ingest your business information into Botaura using any of our native ingestion channels:
File Upload
Upload PDF, DOCX, TXT, and operational guidelines with automatic text extraction.
Website Crawling
Provide your website URL and Botaura crawls pages and subpages automatically.
Manual FAQs
Add custom Q&As and business policies directly into your knowledge base.
AI Embeddings & Vector Processing
Botaura splits your content into contextual chunks and computes high-dimensional semantic vector embeddings.
What are Vector Embeddings?
Embeddings are mathematical vector representations that capture semantic meaning. They enable Botaura to understand user intent and retrieve relevant answers even when the customer doesn't use exact keywords.
We leverage modern embedding models with PostgreSQL + pgvector for sub-second semantic retrieval and enterprise-grade accuracy.
Customize Your AI Chatbot
Customize your AI chatbot to seamlessly reflect your company's visual identity and brand voice.
Embed Anywhere
Ek simple script snippet ke through chatbot ko kisi bhi website par install kar sakte hain.
<script
src="https://botaura.app/widget.js?v=2"
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 automatically qualifies customer conversations into revenue-generating business opportunities.
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.