Author: Shabbir Poonawala

As a developer, I’ve had my fair share of frustration with traditional staffing methods. That’s why I decided to build a Commercial AI Agent using n8n, Vector DBs, and webhooks.

The goal was to create a system that could handle customer interactions with minimal human intervention. With n8n as the workflow automation engine, I integrated Vector DBs for efficient data storage and webhooks for seamless communication.

Now, our AI Agent can process and respond to customer queries in real-time, eliminating the need for extensive training or manual intervention. Shahi Raj can help you build a similar system for your organization.

Want to learn more about the tech stack behind our AI Agent? Reach out to schedule a consultation.

#ShahiRaj #AIDevelopment #N8n #VectorDBs #Webhooks

I recently built a scalable call center solution using n8n, Vector DBs, and our AI Voice Agents. The goal was to create a system that could handle an unlimited number of concurrent calls.

The solution involved using n8n to handle webhooks and API integrations, Vector DBs to store and manage call data, and our AI Voice Agents to answer and qualify calls in real-time.

One of the key challenges was ensuring that the system could scale horizontally. I used n8n’s workflow capabilities to distribute the load across multiple nodes, and Vector DBs to handle the high volume of call data.

The result was a system that could handle 50 concurrent calls without breaking a sweat. And the best part? It was all built using open-source tools and our AI Voice Agents. Learn more about our AI-powered solutions and discover how you can build a scalable call center that meets your business needs.

#ShahiRaj #CallCenter #n8n #VectorDBs

We’ve built a ‘Sales Copilot’ RAG agent to supercharge our sales team’s productivity. In this post, I’ll dive into the technical architecture and implementation details of our Sales Copilot.

Our Sales Copilot integrates with our Vector DBs, leveraging n8n workflows and Webhooks to provide instant, approved responses to technical questions. This enables our junior reps to ask the bot and get the perfect answer instantly.

I’ll walk you through the code logic and architecture behind our Sales Copilot, highlighting the key technologies and integrations that make it work.

Stay tuned for the next part of this series, where I’ll share more about the business impact of our Sales Copilot.

#n8n #VectorDB #SalesCopilot #ShahiRaj

I’ve seen it happen: CEOs pasting sensitive client contracts into standard ChatGPT to get a summary. Stop. You’re potentially training a public model on your private data. Here’s a better approach: Self-Hosted RAG Agents. We spin up a private Vector Database (like Pinecone or pgvector) on your own server. The AI ‘reads’ your data, but never ‘learns’ from it for the public. It lives in a walled garden. You get the intelligence of LLMs without the data leak risk.

vectorDb = Pinecone.create_index('my_index')
rag = n8n.create_workflow('my_workflow')

I recently built a Q&A bot using n8n and Vector DBs for a client. The goal was to create a system that could scan a large number of documents and provide accurate answers to employee queries. Here’s a high-level overview of how I approached the project.

First, I set up a webhook to receive incoming queries from employees. Then, I used n8n to process the query and retrieve the relevant documents from the Vector DB. Finally, I implemented a simple logic to extract the answer from the document and return it along with the page number.

It was a fun project, and I’m excited to see the impact it will have on the client’s internal knowledge management.

Want to learn more about building a Q&A bot? Check out our blog for more technical insights.

#n8n #VectorDBs #QandA

SaaS apps trap your data in their ecosystem, making it difficult to integrate with other tools. But what if you could have a custom bot that connects your ecosystem and gives you a command line for your life? That’s exactly what we do at Shahi Raj.

We build a middleware layer that takes a simple Telegram text and routes it to Google Sheets, Trello, or SQL automatically. It’s not just a chat, it’s a command line for your life. Learn how we can help you build your own second brain.

Here’s an example of how it works:

• Forward invoice to bot: bot saves it to Drive
• Tell bot 'Remind me': bot adds task to Calendar
• Search for PDF: bot finds it in seconds

Want to know more? Let’s chat about how we can help you build your own second brain.

#ShahiRaj #SecondBrain #Python

Why log into a dashboard to check sales? I build n8n workflows that listen for Stripe/Razorpay events and ping a Telegram Bot instantly: ‘💰 ₹5, 000 received from Client X’. I’ll show you how we secure these webhooks so only you get the data.

In this post, I’ll walk you through the n8n workflow setup and the importance of webhooks in your monitoring stack.

I built a tool that automates my SEO audits using n8n and the Google Pagespeed Insights API. Every Monday, it checks my client sites for broken links (404s), verifies the sitemap.xml, and hits the Google Pagespeed API to check the score. If the score drops below 90, I get an alert. Technical SEO requires constant monitoring, not a one-time fix. By automating these audits, I can stay on top of performance issues and make data-driven decisions to improve my clients’ websites.

The tool uses n8n to fetch the data, and then uses the Pagespeed Insights API to get the score. It’s a simple but effective way to stay on top of SEO performance and catch any issues before they become major problems.

You can see the code in action on my GitHub page and learn how to build your own automation tool using n8n and the Pagespeed Insights API.

I’m excited to share the workflow I created to automate our team’s standup:

• Scheduled Trigger (Monday 9 AM)
• Telegram Node (Ask Question)
• Wait for Reply
• Append to Sheet
• OpenAI Node (Summarize)
• Post to ‘General’ Channel

The result is a fully automated management loop. The best part? It was all done using n8n and Telegram. If you’re interested in learning more, Shabbir Poonawala has a detailed guide on his website. #n8n #Telegram #Automation

As the developer behind the Misri Calendar & Weather Bot, I’m excited to share the technical details of our latest update. By integrating multiple services into one seamless experience, we’ve created a powerful tool for our community.

The update leverages n8n’s workflow automation capabilities, Vector DBs for efficient data storage, and Webhooks for real-time updates. The bot’s architecture is designed to handle high volumes of requests while ensuring accurate and up-to-date information.

With this update, we’ve also improved the user experience by simplifying the workflow and adding a local holidays feature. The result is a more comprehensive and user-friendly experience for our users.

At Shahi Raj, we’re passionate about building innovative solutions that make a difference in people’s lives. If you’re interested in learning more about our development process and how we built the Misri Calendar & Weather Bot, stay tuned for future updates.

Learn more about our development process and how you can build similar solutions: https://www.shahiraj.com

Tags: #ShahiRaj #BotDevelopment #TechnicalDeepDive #AutomationSolutions #n8n #VectorDBs #Webhooks