AI Playbook #1: The Email AI-Agent That Turns Hours into Minutes

OPTIMIZE YOUR BUSINESS WITH AI AUTOMATION

Welcome to the inaugural edition of Caveminds AI Playbooks! In this series, expect to get practical tips and insights on implementing AI automation.

Discover strategies and use cases aimed at reducing costs and saving time on workflows.

We believe that every single use case, workflow, and core function at your company can be integrated with AI and then automated to unlock growth at an unprecedented level.

And that’s what we’re here to show.

For this first edition, we share the steps behind the creation of an AI Inbox Agent that we created for one of our clients and we’re using at Caveminds too.

Watch this video to see the story behind this build and the power that will unlock for your business:

If you’d like to get the AI Inbox Agent of this playbook or any other workflow in your company completely implemented and automated by us, book a discovery session with us or hit reply to this email.

Email Agent AI Automation Playbook

The Founder’s Paradox: Scaling Up While Drowning in Emails

Imagine an AI tool that not only understands your communication style but also contextually analyzes and automates email responses.

We built an AI email agent that’s designed to transform the hours you spend responding to emails into minutes, all while ensuring that your responses are personalized, contextually relevant, and secure interactions.

In today's fast-paced world, professionals, especially founders, find themselves buried under an avalanche of emails.

This constant deluge is more than just an annoyance; it's a productivity killer and a source of unending stress.

The Problem

And even worse, a significant portion of this time is spent on irrelevant communications.

This time spent on email management comes with a high opportunity cost of critical activities that you could be doing, like strategic planning, team management, and business development. 

The need for a smarter, more efficient approach isn't just a luxury; it's a necessity.

ROI Analysis

Individual ROI:

For one of our clients, the AI email agent saves them 5 hours per week. Valuing founder time at a conservative rate of $250/hour, translates to a weekly saving of $1,250.

Just take your current hourly rate and multiply that by how much time you currently spend in your inbox each day, and that will be how much money and time you’re saving. You might be surprised by the number.

Team ROI: 

Time Savings Per Employee: Each team member saves up to 5 hours per week by reducing time spent on email management. This is time reallocated to high-value tasks crucial for business growth.

Quantifying the Savings: Assuming an average hourly rate of $50, the weekly saving per employee is $250. For a 100-person team, this amounts to a staggering $25,000 saved every week.

Monthly Financial Impact: Extrapolating these savings over a month reveals an impressive figure of approximately $100,000. 

You see, this is not just a cost-saving but an investment in strategic initiatives and innovation.

The impact extends beyond just financials. It includes reduced stress, increased job satisfaction, and a more focused workforce, contributing to a healthier, more productive work environment.

Over time, these savings compound, leading to substantial gains in operational efficiency, market competitiveness, and scalability for the company.

Core Benefits

• Personalized Email Responses: Tailor-made replies that sound just like you.

• Advanced Context-Aware Management: Understands the essence of every email.

• Automated Templates and Attachments: For swift, efficient communication.

• Round-the-Clock Responsiveness: Keeping you connected 24/7.

• Smart Spam Filtering: It will only respond to emails that are not spam.

• AI Research Agent: Gathers relevant data about business and person to provide a solid response with that information in mind.

• Private and Secure Communications: Confidentiality and safeguarding of sensitive information.

• Categorized Email Triage: Automatically sorts emails by type and urgency and makes the agent respond to those types/categories in certain ways.

• Auto-Escalation Feature: This feature will escalate the email to a human (you or a team member) if it feels it cannot create an email draft accurately enough and needs human input.

• Automated Follow-Ups: Keeps track of your email conversations and sends follow-ups as needed, ensuring continuous engagement.

The Implementation

• Base Setup (1-2 Days): Integration with platforms like Gmail, setting up basic functionalities.

• Advanced Training (4-7 Days): The AI learns from your sent emails, building a customized response database.

• Full Agent Deployment (1-2 Weeks): AI categorizes incoming emails and handles them accordingly.

The Tech Stack

• Make: for integrating and automating workflows between various applications and services like Gmail and OpenAI.

• Open AI API: for creating accurate and coherent email drafts and replies.

• Relevance AI: for analyzing email content and generating intelligent response suggestions based on past interactions and FAQs.

• Custom Python scripts: for processing and cleaning email data, and for implementing specific automation logic tailored to the system's needs.

The Building Process

There are three variations of this build. 

• Basic: this includes an AI creating drafts for your emails but has little to no context on your previously sent emails.

• Advanced: features in this one include:

  • Creating a RAG system, aka a knowledge base of all your sent emails.

  • Building a knowledge base with 100's to 1000's of FAQ's about you based on your sent emails.

  • Having GPT-3.5 or 4 call on that knowledge base dynamically to create the perfect email draft for the reply.

• Expert: this one includes AI agent features that make possible:

  • Not only drafts emails but also sends automated replies, making possible the full automation of the process.

  • Agents that make possible a higher level of data manipulation and customization.

  • Integration with GitHub for ongoing development and deployment of updates.

Let’s get on to them…

Creation of the Basic version:

This is a basic version where you don’t need any coding experience. You can watch the full tutorial by Jacob here, and follow the step-by-step below:

1. Log in to Make.com (or an alternative like Zapier) and create a new scenario.

2. Add a Gmail Module to Watch Emails:

   • Configure the module to watch for emails. For instance, set up a filter for important and unread emails starting from the current time.

3. Add an OpenAI module to your scenario:

   • Configure the module to create a completion. Choose a model, such as GPT-3 or GPT-4.

   • Set the role for the model as "email draft reply creator".

   • Define the task for the model, such as creating an email draft based on the given context.

   • Provide More Context to the OpenAI Module, pasting some of your emails into the module to help the AI understand your tone and style of email communication.

4. Configure Message Content:

   • Add fields for 'item' and 'user'.

   • For the message content, use an example email's text content.

5. Add a Special Gmail Module for Draft Replies and configure the module with the necessary fields:

   • Gmail message ID.

   • Email address from which the message was received.

   • Content created by the OpenAI module.

6. Set Up Confidentiality Mode to ensure Make.com does not log any data.

7. Start the Scenario.

Creation of the Advanced version:

This advanced setup is more intricate, involving multiple scripts and platforms. It's designed to create personalized, context-aware draft replies, leveraging both email data and AI technology.

Steps Involved:

• Complex workflow setup in Make.com, including full automation of replies.

• Advanced data processing with custom Python scripts.

• Integration of AI for content analysis and response generation.

• Deployment of the system in a production environment.

Knowledge Required:

• In-depth understanding of Make.com, including complex module integration.

• Python knowledge for custom data processing and script writing.

• Familiarity with AI concepts and OpenAI’s capabilities.

• Knowledge of cloud deployment, monitoring, and version control with GitHub.

Watch the full step-by-step explanation by Jacob on how to configure your advanced email drafter by clicking below:

If you have some coding knowledge this should be something you can set it up yourself or ask your dev team to do it. Also, you can always reach out to us an we can get it done for you or hit reply to this email.

Creation of the Expert version:

These are the key requirements for building the expert version:

1. Understanding of AI Agents and Python Code.

2. Use of Make.com for Automation for integrating APIs.

3. Script for Robotizing Email Replies: for escalating the automation level from drafting to sending.

4. Deployment in a Production Environment: This involves deploying the code to a server or a cloud platform.

5. Account Creation and Deployment on Render.com: for deploying the automation system and the 'inbox agent', which is the key component of the system.

6. Connection to GitHub: This connection is used for version control and for deploying updates through Render.com.

7. Monitoring and Logging: Ability to monitor the logs and performance through Render.com for real-time insights.

8. Knowledge of Email API (Gmail Agent): for the system to interact with email services.

9. Capability to Scale the System: The system should be designed in a way that it can be scaled up as required, especially if it is initially set up for a small team.

Reach out to us for more details on how to deploy the Expert version or if you’d like to get it done for you or hit reply to this email.

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That’s all for today’s playbook. Stay tuned for our next one, where we break down another case study that you can implement in your business!