Blog

  • Building the Digital Spine: A Technical Deep Dive into Custom n8n Workflows

    Hello fellow developers! Today, I’d like to share with you a project I recently worked on – a custom n8n workflow designed to automate data routing and syncing for a client’s operations.

    Problem Statement: The client was manually ‘copy-pasting’ data between WhatsApp, Sheets, and their CRM, which was causing a bottleneck in their operations. We needed to build a system that could automate this process and free up their team’s time.

    Technical Solution: I designed a custom n8n workflow using a combination of Webhooks, Vector DBs, and Debian 12/AWS Mumbai server hosting. This setup allowed us to route 800+ shipping updates seamlessly and sync leads from their web widget.

    Code Logic: The custom n8n workflow is built using a series of nodes that trigger and update each other in real-time. I’ll be sharing more about the code logic and architecture in a future post.

    Want to learn more about building custom n8n workflows? Get in touch with us today, and let’s discuss your project requirements.

  • Building the Zero-Effort Content Engine with n8n, Vector DBs, and Webhooks

    I’m excited to share my latest project, ProductStudioAI, which leverages the power of n8n, Vector DBs, and webhooks to create a seamless content creation experience.

    With n8n, I built a workflow that takes a single photo as input and generates 8 high-quality shots in just 3 minutes. I used Vector DBs to store and retrieve the photos, and webhooks to integrate with our Telegram bot.

    The result is a 24/7 professional studio that’s accessible to anyone, anywhere in the world.

    Check out the code on GitHub and learn how to build your own zero-effort content engine.

  • Building the Amazon Seller’s Shield: A Technical Deep Dive

    As a developer, I’ve always been fascinated by the challenges faced by Amazon sellers. That’s why I built @SmartSourcingAI_Bot, a solution that uses machine learning to identify if a niche is locked down by giants.

    The bot is built using n8n, a popular workflow automation tool. It integrates with various data sources, including Vector DBs, to gather insights on market trends and competitor activity.

    When a seller uses the bot, it checks if the niche is owned by a major brand, such as Milton or Prestige. If it is, the bot sends a notification to the seller, advising them to explore alternative options.

    We’ve also implemented a Webhook system to enable real-time updates and notifications. This ensures that sellers always have the latest information at their fingertips.

    Want to know more about the technical details of the bot? Reach out to me and let’s chat.

  • Building ProductStudioAI: A Technical Deep Dive into Our AI-Powered Product Photography Solution

    As a developer, I’m excited to share the technical details behind our latest innovation – ProductStudioAI, the AI-powered bot that generates professional product images in under 3 minutes. This post will take you through the tech stack, architecture, and code logic that make this possible.

    Our solution is built on top of n8n, a powerful workflow automation tool, and Vector DBs, a high-performance database that enables fast image processing. We’ve also integrated Webhooks to streamline communication between the bot and Telegram. The result is a seamless user experience that produces high-quality images without any manual intervention.

    Want to know more about the tech behind ProductStudioAI? Check out our blog for the full technical deep dive.

  • Building the ShahiRaj Data Collector: A Real-time Field-to-Office Bridge

    I’m excited to share my latest project, the ShahiRaj Data Collector, a real-time field-to-office bridge built using n8n workflows, Zoho Creator forms, and AWS Mumbai as the backend. The goal was to create a seamless experience for field staff and empower management with instant visibility.

    The architecture involves a user-friendly Android app for field staff to submit reports, which are then processed by n8n workflows and stored in Zoho Creator forms. This data is then pushed to our AWS Mumbai backend, where it’s aggregated and visualized in a master dashboard.

    One of the key challenges I faced was ensuring real-time data processing and visibility. I achieved this by leveraging n8n workflows and AWS Mumbai services. The result is a robust and scalable solution that bridges the gap between site and office instantly.

    Want to know more about the technology behind the ShahiRaj Data Collector? Reach out to me directly.

    #ShahiRaj #DataCollector #n8n #ZohoCreator #AWSMumbai #RealTimeProcessing

  • Building the ‘Friday Friction’ Fix: A Technical Deep Dive into Custom n8n Workflows

    I recently built a Custom n8n Workflow for a client that aimed to automate their data reconciliation process. The goal was to free up their team’s Fridays from tedious manual work, and I’m excited to share the technical details of how we achieved this.

    The workflow was built using n8n’s robust API and integrated with Vector DBs for real-time data syncing. Webhooks were also used to trigger the workflow when new data was available.

    The result was a seamless automation process that cleaned up the client’s data in real-time, freeing up their team to focus on high-priority tasks.

    Ready to dive deeper into the technical details? Check out our blog for more insights on building Custom n8n Workflows.

  • Building the 24/7 Gatekeeper: A Technical Deep Dive into Our AI Lead Gen Widget

    Building the 24/7 Gatekeeper: A Technical Deep Dive into Our AI Lead Gen Widget

    As a developer, I’m excited to share our technical approach to building an AI-powered lead gen widget that acts as a front-line gatekeeper.

    We’re using n8n to integrate with Vector DBs and Webhooks to create a seamless qualification process. The widget engages every visitor, asks the right questions, and qualifies them instantly.

    Check out our tech stack and learn how we’re empowering businesses to focus on high-value opportunities.

  • Building a Custom AI Brain using n8n and Vector DBs

    I was recently tasked with building a custom AI brain for a client, and I decided to use n8n and Vector DBs to create a private, internal ‘Google’ for their company’s specific data.

     

    Here’s a high-level overview of the architecture I used:

     

      n8n                                                                                           Vector DBs

     

    I used n8n to create a workflow that fetches data from various sources, and then used Vector DBs to create a knowledge graph that provides accurate, context-aware answers to the user’s queries.

     

    One of the challenges I faced was handling the data integration and ensuring that the knowledge graph was up-to-date. I used Webhooks to handle the data integration and ensure that the knowledge graph was always current.

     

    Overall, building this custom AI brain was a challenging but rewarding project, and I’m excited to see how it will benefit the client’s business.

     

    Learn more about our Custom RAG AI Agents and how they can transform your business and make your company’s expertise more accessible.

  • Building the Instant Expert: A Technical Deep Dive into Our AI Support Widget

    As a developer, I’ve seen firsthand the pain of answering the same five questions over and over. That’s why I built the Shahi Raj AI Support Widget, designed to absorb 70% of routine queries instantly, based on your own knowledge base. Let me take you through the technical architecture behind this solution.

    Our AI Support Widget is built on top of a secure Debian 12 setup, utilizing n8n workflows, Vector DBs, and webhooks to provide a seamless and efficient experience for your customers. By leveraging machine learning algorithms, we’re able to identify and respond to common queries, freeing up your human agents to focus on high-value customer issues.

    Want to know more about the tech stack behind our AI Support Widget? Check out our developer blog for more technical insights.

    #ShahiRaj #AIProduct #TechnicalDeepDive

  • Building the Capital Guard: A Technical Overview

    I’m excited to share with you the technical details behind our Capital Guard solution.

    Our AI-powered solution uses a combination of natural language processing (NLP) and machine learning algorithms to perform ‘Brand Moat Detection’ instantly.

    Here’s a high-level overview of the architecture:

    • n8n workflow automation platform for data integration and processing
    • Vector DB for fast and efficient data storage
    • Webhooks for real-time notifications and updates

    Our AWS Mumbai infrastructure provides the scalability and reliability needed to process large amounts of data in real-time.

    Want to learn more about the technical details behind our Capital Guard solution? DM me and let’s discuss.

    #ShahiRaj #CapitalGuard #TechnicalOverview #SmartSourcingAI_Bot