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WWT Research • Applied Research Report
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Part 2: Inside RFP Assistant — Summarizer and Qualification Workflow

The second article in a series exploring RFP Assistant, a GenAI-powered tool designed to increase the efficiency and impact of WWT's Proposal team. This article focuses on the tool's summarization, qualification and chat applications. Readers interested in LLM-powered generation, a RAG-powered chatbot and data science-powered insights will find value in how the combination of the three enables this tool.

This is part two of three in a series about WWT's RFP Assistant, an innovative GenAI tool designed to streamline the proposal response process. 

This article describes the functionalities of RFP Assistant, focusing on its summarization, qualification and chat features, which aid proposal managers in handling requests for proposals (RFPs) efficiently:

  • Summarization: The summarization feature extracts key information, requirements, deadlines and legal considerations from RFPs, saving proposal managers time by focusing on three main areas: introduction and background, timeline and legal considerations.
  • Qualification: The qualification feature identifies similar past RFPs from internal databases, calculating similarity scores and historical win rates to help decide whether to pursue a bid.
  • Chat: The chat feature allows proposal managers to ask specific questions about the RFP documents, using embeddings and a RAG framework to provide relevant answers.

Keep reading to learn how these features and more were developed and how RFP Assistant provides business value to the WWT Proposal team. 

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