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.

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.

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

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

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.

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.

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

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

I built a Sunday Briefing workflow using n8n and Vector DBs to capture month-end reflections and organize ‘Must-Do’ lists. The workflow integrates with Debian 12 and AWS to assist with scheduling and expense tracking.

The architecture involves using n8n’s workflow automation features to fetch data from Vector DBs, which stores the user’s reflections and tasks. Webhooks are used to trigger the workflow on Sundays, ensuring a seamless ‘Sunday Reset’ experience.

Want to see the code? Check out the GitHub repo or contact us for more information on how to build your own Sunday Briefing workflow.

#n8n #VectorDBs #SundayBriefing #WorkflowAutomation #ShahiRaj

I built the SmartSourcingAI_Bot from the ground up, using a combination of n8n, Vector DBs, and Webhooks to perform ‘demand gating’ and identify low-velocity products. The system uses AWS Mumbai infrastructure to process data instantly and provide a ‘safe buy price’ for sourcing meetings. By integrating with Amazon’s API, the bot can stop analysis when velocity is too low, preventing unnecessary resource consumption. Check out the code and learn how to build a similar system for your clients. #ShahiRaj