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AI / GenAI

GenAI Conversational Insights

RAG-based system for extracting actionable insights from audio and chat conversations using LLMs.

Problem

Large volumes of conversational data go unanalyzed, missing valuable patterns and insights.

Solution

Built an end-to-end pipeline: speech-to-text → normalization → RAG retrieval → LLM analysis → structured insights.

Architecture

1

Audio/Chat Input

Multi-modal input collection

2

Speech-to-Text

Audio transcription

3

Normalization

Text preprocessing

4

RAG Retrieval

Context-aware document retrieval

5

LLM Processing

Insight generation

6

Evaluation

Quality assessment

Technologies

PythonLLMRAGSpeech-to-TextNLP

Lessons Learned

  • RAG significantly improves LLM response quality over pure generation

  • Evaluation frameworks are essential for production LLM systems