Webinar on Automation and AI in Business

Introduction

• Webinar series on using automation in business with AI.
• Hosted by TB from Make It Future.
• Key achievement: Saved 150 hours/month equivalent to $30k in savings through automation.

Agenda Overview

1. Introduction to building a chatbot using AI.
2. Practical demonstration of building the chatbot.
3. Explanation of the platform Make and its uses.

Introduction to Make

• Make is an automation platform that also incorporates AI.
• Connects various apps and facilitates automation.

Make It Future

• Automation agency with expertise in no-code platforms like Make, Airtable, and HubSpot.
• Operations based in Romania with a global presence.

TB's Journey

• Started with a company called Blue Coffee Roaster.
• Faced challenges with e-commerce operations and retargeting.
• Discovered HubSpot and Integromat (now Make) to automate processes.
• Transitioned into providing automation services.

Use Case: Blue Coffee Chatbot

• Aim to improve customer experience and automate customer queries.
• Challenges included manual response to customer inquiries about orders.
• Solution involved AI chatbot integrated with business systems.

Building an AI Chatbot

1. User messages the AI agent.
2. AI decides response based on its knowledge or queries a business-specific database (RAG - Retrieval-Augmented Generation).
3. Uses functions to take actions or retrieve specific information from business systems.
4. Compatible with various communication platforms (WhatsApp, Slack, etc.).

Key Concepts

Live Connections

• Allows AI to connect to any system and perform actions.
• Can execute actions like creating orders or retrieving status updates.

RAG (Retrieval-Augmented Generation)

• Enhances AI responses with business-specific data.
• Utilizes vector databases to provide accurate and informed responses.

Practical Demonstration in Make

• Setup involves configuring webhooks and defining AI assistant functions.
• Uses various modules in Make to create and manage chatbot interactions.
• Demonstrated live testing and deployment of the chatbot.

Benefits and Challenges

• Saves significant time and costs.
• Improves customer service and experience.
• Data privacy maintained by controlling information shared with AI.
• Challenges include managing hallucinations and ensuring accurate responses.

Additional Insights

• Fine-tuning AI responses for better accuracy using RAG.
• Make allows for rapid testing and deployment of different automation strategies.

Conclusion

• TB encourages exploration of Make and AI functions.
• Upcoming webinars and resources will be shared with attendees.