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ExtractFromFile Automate

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ExtractFromFile Automate streamlines the RFP response process by automatically extracting questions from submitted documents, generating tailored responses using AI, and organizing everything in a dedicated Google Doc. It enhances efficiency by notifying the team via email and Slack once the task is complete, allowing for quicker turnaround times on RFPs and improved collaboration.

Workflow Overview

ExtractFromFile Automate streamlines the RFP response process by automatically extracting questions from submitted documents, generating tailored responses using AI, and organizing everything in a dedicated Google Doc. It enhances efficiency by notifying the team via email and Slack once the task is complete, allowing for quicker turnaround times on RFPs and improved collaboration.

This workflow is designed for:

  • Sales Teams: Looking to streamline the response process for RFPs, allowing for quicker and more efficient replies.
  • Project Managers: Who need to manage multiple RFPs simultaneously and ensure all responses are documented accurately.
  • Business Development Professionals: Aiming to enhance their proposal quality using AI-generated insights and answers.
  • Technical Teams: Responsible for implementing and maintaining automated workflows to improve operational efficiency.

This workflow addresses the challenge of manually extracting questions from RFP documents and generating responses efficiently. By automating the process, it reduces the time spent on document handling, enhances accuracy in responses, and ensures that no critical questions are overlooked. The integration of AI allows for contextual answers, improving the quality of submissions and increasing the chances of winning bids.

  1. Receive RFP Document: The workflow starts by receiving an RFP document via a webhook. Users must submit the document through an API request.
  2. Extract Data: The document is processed to extract relevant data using the ExtractFromFile node, focusing on PDF files.
  3. Set Variables: Key variables such as document title, filename, and the reply-to address are set for later use.
  4. Create RFP Response Document: A new Google Docs document is created to store the responses, ensuring each RFP has a dedicated space for answers.
  5. Extract Questions: AI is employed to identify and extract questions from the RFP, regardless of formatting, using the LangChain capabilities.
  6. Generate Answers: For each extracted question, the workflow loops through and generates answers using an OpenAI Assistant, ensuring contextually relevant responses.
  7. Record Answers: Each question and its corresponding answer are recorded in the Google Docs document.
  8. Add Metadata: Metadata including the document title, generation date, and requester details are added to the document for clarity and tracking.
  9. Send Notifications: Upon completion, notifications are sent via email and Slack to inform the team and the requesting user that the RFP response is ready.

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Quick Info

Categories
Communication & Messaging
Complex Workflow
+1
Complexity
complex

Tags

webhook
advanced
api
integration
complex
sticky note
files
storage
+8 more

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