Building a Stable and Intelligent Chat Automation System

Introduction

At Innovate Web, we specialize in creating scalable and innovative digital solutions. In this article, we’re diving into one of our most technically challenging projects: building a robust browser extension and AI-driven chat automation system.

The Business Challenge

The company approached us with a core problem: their chat automation extension was unstable. Conversations were getting disrupted due to website auto-refreshes, leading to the bot stopping unexpectedly. Additionally, there was a need for prioritization in conversations, especially when closing a sale. Another crucial aspect was the efficient handling of media files—models needed the ability to sell content based on the ongoing conversation’s mood.

Technical Approach

The company’s system was built from the ground up, featuring:

• A back-office to manage model’s data
• A server handling AI-driven responses and content sales
• A Chrome extension facilitating real-time interaction on the platform

Building a Robust Chrome Extension

To ensure stability, we developed a state persistence system that allowed the bot to automatically restart with its last known state whenever an auto-refresh occurred. Additionally, we implemented a queue system that prioritized conversations where sales were being finalized, ensuring smoother transactions and higher conversion rates.

Key technologies used:

• JavaScript with Chrome’s Manifest system
• Chrome Local Storage for persistent data handling
• DOM interaction for fetching unread conversations and responding dynamically

AI Integration & Challenges

The AI system was responsible for generating contextual, engaging replies while also adapting to different conversation tones. Key AI components included:

• Conversation Summaries & User Profiles: We built a system to generate conversation “resumés,” storing user details like name and preferences to create personalized interactions.
• Overcoming AI Content Censorship: One major challenge was handling large prompts containing adult content, as many AI models enforce strict censorship rules. Our solution? Fine-tuning Gemini AI to generate responses while staying within acceptable moderation guidelines.

Key Takeaways & Lessons Learned

This project provided valuable insights into building AI-driven automation solutions:

• AI with Memory – Storing conversation history and user preferences greatly enhances engagement and personalization.
• Sentiment Analysis – Understanding conversation tone enables dynamic adjustments in chatbot behavior.
• Lifecycle & Stability – A bot must be resilient to external interruptions, maintaining state across browser refreshes.
• Sales-Optimized Automation – AI-driven automation doesn’t just reduce costs—it actively boosts conversions by engaging users more effectively.