AI Meeting Minutes & Content Generator

Transform your meeting attachments into actionable summaries, follow-up emails, and blog posts with AI. This workflow automates content creation from your meeting files, saving you time and boosting productivity.

How the AI Flow works - AI Meeting Minutes & Content Generator

Flows

How the AI Flow works

File Attachment Upload.
User uploads meeting audio, video, or document attachments.
Extract File Content.
The workflow retrieves and processes the content from the uploaded meeting files.
Generate Meeting Minutes.
AI analyzes the extracted content to create structured meeting minutes.
Create Follow-Up Email and Blog Post.
AI generates a follow-up email and a compelling blog post based on the meeting content.
Deliver Actionable Outputs.
The generated minutes, email, and blog post are displayed and ready for the user to copy or share.

Prompts used in this flow

Meeting Minutes Generation Prompt

Prompt instructing the LLM to generate meeting minutes based on provided context from an attachment.

Here is the context of attachment that was attached given as CONTEXT
---CONTEXT
{context}
---

Generate a meeting minutes

Meeting Minutes Output Template

Prompt template formatting the meeting minutes output with the given context.

## Meeting Minutes
{context}

Follow-Up Email Generation Prompt

Prompt instructing the LLM to generate a follow-up email using the context extracted from the attachment.

Here is the context of attachment that was attached given as CONTEXT
---CONTEXT
{context}
---

Generate a followup email

Follow-Up Email Output Template

Prompt template formatting the follow-up email output with the generated context.

## Followup Email✉️
{context}

Blog Post Generation Prompt

Prompt instructing the LLM to generate a compelling blog post based on the provided context.

Here is the context of attachment that was attached given as CONTEXT
---CONTEXT
{context}
---

Generate a compelling blog

Blog Output Template

Prompt template formatting the blog output with the generated context.

## Blog📄
{context}

Components used in this flow

Below is a complete list of all components used in this flow to achieve its functionality. Components are the building blocks of every AI Flow. They allow you to create complex interactions and automate tasks by connecting various functionalities. Each component serves a specific purpose, such as handling user input, processing data, or integrating with external services.

ChatInput

The Chat Input component in FlowHunt initiates user interactions by capturing messages from the Playground. It serves as the starting point for flows, enabling the workflow to process both text and file-based inputs.

See ChatInput

File Retriever

The File Retriever component in FlowHunt lets you bring files into your workflow and convert them into documents for further processing. It supports strategies for handling multiple documents and can use OCR on images within files, making it ideal for extracting and transforming information from a wide variety of file types.

See File Retriever

Prompt Component in FlowHunt

Learn how FlowHunt's Prompt component lets you define your AI bot’s role and behavior, ensuring relevant, personalized responses. Customize prompts and templates for effective, context-aware chatbot flows.

See Prompt Component in FlowHunt

Generator

Explore the Generator component in FlowHunt—powerful AI-driven text generation using your chosen LLM model. Effortlessly create dynamic chatbot responses by combining prompts, optional system instructions, and even images as input, making it a core tool for building intelligent, conversational workflows.

See Generator

Chat Output

Discover the Chat Output component in FlowHunt—finalize chatbot responses with flexible, multi-part outputs. Essential for seamless flow completion and creating advanced, interactive AI chatbots.

See Chat Output

Flow description

Purpose and benefits

Overview

The AI Meeting Report Generator workflow is designed to automate the transformation of meeting attachments (such as audio or video files) into actionable written content. This includes generating detailed meeting minutes, follow-up emails, and engaging blog posts, all tailored from the context extracted from the original meeting materials. The process is highly scalable and eliminates repetitive manual work, making it ideal for organizations that want to streamline meeting documentation and communication.

Step-by-Step Flow

1. User Onboarding and Input

  • Welcome Message: When the chat session opens, the user is greeted with a friendly welcome message outlining the steps:

    1. Attach your meeting audio or video.
    2. Receive detailed meeting minutes.
    3. Get a ready-to-send follow-up email.
    4. Obtain a blog post summarizing the meeting.

  • File Upload: The user uploads a meeting attachment (audio, video, etc.) via a chat interface.

2. Extracting Content

  • File Content Extraction: The uploaded file is processed to extract its content. This step may involve transcription (for audio/video), OCR (for scanned docs), or direct text extraction (for text-based files).

3. Generating Outputs

For each type of output (meeting minutes, follow-up email, blog), the workflow follows a similar pattern:

A. Meeting Minutes

  1. Prompt Preparation: The extracted context is embedded into a prompt template instructing the AI to generate meeting minutes.
  2. AI Generation: A large language model (LLM) processes the prompt and generates a draft of meeting minutes.
  3. Formatting: Another prompt formats the output into a standardized section titled “Meeting Minutes”.
  4. Display: The result is sent to the chat output for the user to review or copy.

B. Follow-Up Email

  1. Prompt Preparation: The same context is used in a prompt instructing the AI to generate a follow-up email.
  2. AI Generation: The LLM creates a draft email.
  3. Formatting: The output is wrapped in a section titled “Followup Email”.
  4. Display: The generated email is displayed for the user.

C. Blog Post

  1. Prompt Preparation: The context is used in a prompt for the AI to create a blog post.
  2. AI Generation: The LLM generates the blog content.
  3. Formatting: The blog post is formatted under a “Blog” header.
  4. Display: The blog post is presented to the user.

The workflow structure ensures each content type is generated independently and in parallel, maximizing efficiency.

Workflow Structure

StepInputProcessingOutput
User OnboardingChat openedWelcome message widgetGreeting in chat
File UploadFile attachmentFile content extractionRaw meeting content
Meeting MinutesExtracted contextAI prompt → LLM → Formatting promptMeeting minutes text
Follow-Up EmailExtracted contextAI prompt → LLM → Formatting promptFollow-up email text
Blog PostExtracted contextAI prompt → LLM → Formatting promptBlog post text

Note: All three outputs are displayed in the chat interface for immediate access and use.

Benefits & Use Cases

  • Scalability: Handles any number of meetings without additional human effort.
  • Consistency: Ensures all meeting documentation follows a standard, professional format.
  • Speed: Instantly generates all deliverables after file upload.
  • Versatility: Works with different file types (audio, video, documents).
  • Automation: Reduces administrative overhead, freeing up time for high-value tasks.
  • Useful For:
    • Project managers and team leads automating meeting follow-ups.
    • HR or operations teams needing standardized documentation.
    • Content creators wishing to repurpose meeting discussions as blog posts.

Conclusion

The AI Meeting Report Generator is a powerful, automated toolchain for turning raw meeting files into structured, actionable, and shareable written assets. By streamlining these processes, it not only saves time but also ensures that critical meeting insights are captured, communicated, and repurposed effectively across the organization.

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