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AI-Powered Customer Support Platform

Tech Stack: RAG, Python, Docker, PostgreSQL

Background: A SaaS company needed an AI-driven chatbot to automate customer support and handle queries.

Challenge: The company struggled with high support costs and slow query resolutions.

Solution: An RAG (Retrieval-Augmented Generation) chatbot was implemented using Python and PostgreSQL, with Docker for containerized deployment.

Impact:

  • Cost Reduction: Support costs reduced by 25%.
  • Efficiency: Resolved 60% of queries instantly.
  • Satisfaction: Increased CSAT by 15%.

Tech Stack: RAG, Python, Docker, PostgreSQL Background: A SaaS company needed an AI-driven chatbot to automate customer support and handle queries. Challenge: The company struggled with high support costs and slow query resolutions. Solution: An RAG (Retrieval-Augmented Generation) chatbot was implemented using Python and PostgreSQL, with Docker for containerized deployment. Impact:

Tech Stack: RAG, Python, Docker, PostgreSQL Background: A SaaS company needed an AI-driven chatbot to automate customer support and handle queries. Challenge: The company struggled with high support costs and slow query resolutions. Solution: An RAG (Retrieval-Augmented Generation) chatbot was implemented using Python and PostgreSQL, with Docker for containerized deployment. Impact: