Intelligent sales assistant

An intelligent sales assistant powered by LLM, helping sales teams analyze calls, extract insights, and close deals faster. 🚀

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Intelligent Sales Assistant

Inspiration

I was inspired by the potential of AI to transform sales processes, making them more efficient and data-driven. The idea of using an LLM-powered assistant to analyze sales calls and provide actionable insights felt like a game-changer.

What it does

DealWise AI is an intelligent sales assistant that:

  • Analyzes sales calls in real time
  • Extracts key insights such as objections, customer sentiment, and follow-up actions
  • Summarizes conversations and suggests next steps
  • Helps sales teams close deals faster by providing AI-powered recommendations

How I built it

I completed the introductory quickstart from the "How to build an LLM-powered Agent in < 5 minutes on Snowflake" workshop during GHW Data Week. Following the step-by-step instructions from the workshop repository, I used Snowflake, Streamlit, and an LLM to build this sales assistant.

Challenges I ran into

  • Initially faced issues with SSE client compatibility, which caused response parsing errors. Upgrading the library resolved the issue.
  • Understanding how to best structure queries for summarizing sales calls efficiently.
  • Optimizing the pipeline to process data quickly while maintaining accuracy.

Accomplishments that I'm proud of

  • Successfully integrating an LLM with Snowflake to analyze and summarize sales calls.
  • Overcoming technical challenges related to streaming responses.
  • Completing the quickstart and applying it to a real-world sales assistant use case.

What I learned

  • How to build and deploy an LLM-powered agent using Snowflake.
  • The importance of structured data queries for efficient AI-powered analysis.
  • Debugging and troubleshooting API response issues in a streaming context.

What's next for Intelligent Sales Assistant

  • Enhancing the model to provide deeper insights, such as predictive deal outcomes.
  • Adding multi-language support for global sales teams.
  • Integrating with CRM platforms for seamless workflow automation.
  • Improving the UI/UX with more interactive and customizable dashboards.

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