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Retrieval: Overview

Retrieval-Augmented Generation (RAG) is an important component for creating accurate, reliable AI applications. Teammately's approach automates and simplifies the entire RAG pipeline through our AI Agent, reducing hallucinations caused by noisy data and inefficient retrieval processes.

Traditional RAG implementations require manual configuration of multiple components which can be automated:

  • Document Processing
  • Contextual Chunking
  • Vector Indexing
  • Query Processing

The Agentic approach means you can simply provide your goal and data—our AI Agent handles the complex implementation details automatically.

Hallucination Prevention Focus​

Hallucinations in AI systems frequently stem from poor quality data and retrieval failures. Teammately addresses main root causes like Data Quality, Context Preservation and Retrieval Optimization.

Integration with Generation Pipeline​

Teammately's RAG system integrates as Knowledgebooks with our Generation capabilities. This approach allows to deliver more accurate, reliable, and contextually appropriate AI responses.