RAG Retrieval-Augmented Generation
Retrieval-Augmented Generation (RAG) combines information retrieval with language generation so responses are grounded in trusted data instead of model memory alone. It improves factual accuracy, reduces hallucinations, and enables domain-specific answers across documents, knowledge bases, and enterprise content while remaining scalable, updatable, and practical for real-world AI applications.
Date : 21 February
Location : Online
₹
Price : 499 ₹0
Registrations Closed !
# Audience
What you'll learn
The CBX experience delivers outcomes that matter at scale.
End-to-end RAG workflow.
Data ingestion and chunking basics.
Embeddings and vector search.
Retriever and chain design.
Hallucination reduction methods.
RAG evaluation and monitoring.
Skills you'll gain
Build complete RAG pipelines fast
Design chunking for better recall
Choose embeddings for relevance
Tune retrievers for precision
Ground answers with source docs
Reduce hallucinations in output
Evaluate RAG with key metrics
Monitor quality using tracing tools
# endless features
Packed with useful features
The CBX experience delivers outcomes that matter at scale.
Context-Aware Retrieval
Finds the most relevant chunks from your documents before generation, so answers stay grounded in real sources instead of guesswork.
Hallucination Reduction
Uses retrieved evidence to improve factual accuracy and significantly lower unsupported or fabricated responses in production use cases.
Live Knowledge Updates
Lets you update system knowledge by refreshing documents/indexes without retraining the base model, making maintenance faster and cheaper.
Traceable Responses
Enables source-linked outputs and evaluation workflows, helping teams verify answers, audit behavior, and improve trust in AI responses.
# Completion certificate
Earn a Verified Certificate of Completion
The CBX experience delivers outcomes that matter at scale.