Author: Shabbir Poonawala

I recently built a scalable AI e-commerce tracker using n8n, Vector DBs, and Webhooks. The goal was to create a system that could handle 800+ monthly updates on our AWS Mumbai server without breaking a sweat.

The system connects directly to our Shipmozo/BigShip accounts, triggering an automated update via WhatsApp the moment a status changes (Dispatched, Out for Delivery, Delivered). We’ve optimized the workflow to minimize latency and ensure seamless updates.

The tech stack includes:

• n8n for workflow automation
• Vector DBs for real-time data storage and retrieval
• Webhooks for instant updates

Check out the ShahiRaj blog for more insights into our e-commerce automation solutions.

This post is part of our Developer Log, where we share technical expertise and behind-the-scenes stories.

I recently had the opportunity to architect and deploy a production-grade digital workforce using n8n and AWS. The result was a seamless migration of our 400+ n8n workflows and AI agents to a dedicated AWS server in Mumbai.

Read the full story on how we achieved near-zero latency, reliability, and security for our WhatsApp and Voice bots.

I’d love to share more about the tech stack and architecture behind this project. DM me if you’re interested in learning more about custom n8n workflows and AWS infrastructure.

As a developer, I’m excited to share how we built the Ai Lead Gen Widget using n8n and AWS. Our goal was to create a 24/7 sales agent that could answer complex questions and qualify leads instantly.

We started by setting up a n8n workflow that integrates with our AWS-hosted n8n instance. The workflow uses Webhooks to push data directly to your CRM or WhatsApp.

On the frontend, we developed a user-friendly interface that allows users to interact with the sales agent. We used Vector DBs to store user data and n8n’s built-in logic to handle complex questions and lead qualification.

Want to learn more about our development process? Reach out to me and I’ll be happy to share more details.

I recently built an AI Meeting Scheduler for ShahiRaj using n8n and Vector DBs. Here’s a high-level overview of the architecture.

The bot lives in WhatsApp and Telegram, and when a user wants to meet, it uses the n8n workflow to check the user’s Google Calendar in real-time.

The Vector DBs are used to store the user’s availability, and the bot uses this data to offer only the slots the user wants to show.

The bot then handles the confirmation and sends the invite—all inside the chat window.

Since we migrated to our AWS Mumbai backbone, the response time is near-instant.

Check out the code and architecture on my GitHub repository: https://github.com/your-username/ai-meeting-scheduler

I recently built a personal multi-functional bot using n8n, Vector DBs, and Webhooks. In this post, I’ll walk you through the technical details of the project and show you how to create a similar bot for yourself.

As a developer, I wanted to create a system that could help me plan my upcoming week, track expenses from the weekend, and pull research for Monday’s meetings. I chose n8n as my workflow automation tool, Vector DBs for data storage, and Webhooks for real-time communication.

Check out the GitHub repository for the n8n workflow and learn how to integrate it with Vector DBs and Webhooks.

With this setup, I can now plan my week, track expenses, and pull research with just a few clicks. The best part? I can customize the bot to fit my specific needs and workflow.

Stay tuned for a follow-up post where I’ll dive deeper into the technical details of the project and share some best practices for building your own personal multi-functional bot.

#ShahiRaj #n8n #VectorDBs #Webhooks

I recently built a custom AI Voice Agent using n8n and Vector DBs for a client. The goal was to create a system that could understand the intent behind a caller’s inquiry and provide relevant information about their services.

Here’s a high-level overview of how I set it up:

• Set up a n8n workflow to handle incoming calls and route them to the AI Voice Agent.
• Use Vector DBs to store and retrieve information about the client’s services and offerings.
• Implement a natural language processing (NLP) library to understand the caller’s intent and provide relevant responses.

The result was a system that could not only take messages but also book meetings directly into the client’s Google Calendar. Check out our developer resources for more information on building a custom AI Voice Agent.

Want to build a custom AI Voice Agent of your own? DM me for a demo number and I’ll show you how it’s done.

I’ve always been fascinated by the potential of Telegram Bots to transform business operations. As a developer, I’ve worked on numerous projects that aimed to bridge the gap between custom apps and Telegram’s robust ecosystem.

When I built my first Custom Telegram Bot, I realized that it could accomplish 90% of what a custom app does, but at 10% of the cost. This sparked an idea to create a more comprehensive tool that could integrate with multiple web services and provide real-time webhooks for teams.

I started experimenting with n8n and AWS to see if I could create a scalable and secure platform for deploying enterprise tools. The result was astonishing – I could deploy a fully functional tool in just 7 days, a fraction of the time it takes to develop a custom app.

My approach involves embedding custom UI ‘Mini Apps’ within Telegram, leveraging real-time webhooks, and utilizing n8n and AWS for seamless deployment. The best part? Your team already has Telegram installed, eliminating the need for a separate download or installation process.

If you’re struggling with complex workflows or need a mobile interface for your team, I’d love to explore if a Custom Telegram Bot can solve your problems faster. Let’s discuss how we can work together to create a tailored solution for your business.

I’ve worked on several projects where the client needed a custom mobile solution. At ShahiRaj Automation, we use a combination of n8n and Vector DBs to build scalable and efficient mobile apps.

One of the projects I worked on was building a custom Telegram bot using n8n and webhooks. The bot was designed to provide instant alerts and simple commands, perfect for situations where speed is of the essence.

However, for more complex use cases, we use a branded Android APK designed for field staff. This APK offers secure logins, offline-capable forms, and complex data reporting using Vector DBs.

One of the benefits of our approach is that we don’t have to worry about Play Store headaches and high costs associated with traditional app development.

With ShahiRaj Automation, you can say goodbye to long development cycles and hello to seamless workflows and secure data hosting at portal.shahiraj.com.

Get in touch with us today to learn more about our custom mobile solutions and discover how we can help you build the perfect mobile app for your needs.

#ShahiRaj #CustomMobileSolutions #MobileAppDevelopment #n8n

I recently built a custom Telegram bot for a client that acts as his company’s ‘Nerve Center.’ Here’s a technical breakdown of how I achieved this using n8n, Vector DBs, and Webhooks.

The bot is built on our new AWS stack and queries the client’s databases to retrieve essential information. I used n8n to create a workflow that fetches data from the databases and sends a response back to the Telegram bot.

The Vector DBs played a crucial role in this project, as they allowed for efficient data retrieval and processing. I also leveraged Webhooks to enable real-time updates and notifications.

Want to learn more about building your own ‘Nerve Center’ bot? Check out our custom bot solutions and let’s get started!

In this article, we’ll delve into the technical aspects of building a digital workforce using n8n workflows and AWS infrastructure. We’ll explore how our systems can autonomously process e-commerce updates, manage production-grade workflows, and integrate with Voice and WhatsApp APIs.

We’ll examine the architecture of our agentic workflows and discuss the key components that enable our systems to ‘do’ rather than just ‘chat.’ This includes the use of n8n’s workflow automation capabilities, Vector DBs for efficient data storage, and Webhooks for seamless API integrations.

Get hands-on with our technical expertise and learn how to build a digital workforce that can automate complex tasks.

#n8n #AWS #AgenticAI #DigitalWorkforce