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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
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RAG significantly improves LLM response quality over pure generation
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Evaluation frameworks are essential for production LLM systems