Blog

  • Building a Pocket-Sized Command Center: An Architectural Overview

    At Shahi Raj, we’ve developed an AI Personal Assistant Bot that integrates with Telegram and WhatsApp, providing a seamless experience for users.

    The bot is built using our high-performance Debian 12 production environment, ensuring scalability and reliability.

    From a technical standpoint, the bot utilizes n8n for workflow automation, Vector DBs for data storage, and Webhooks for real-time updates.

    Want to see how we’ve implemented this architecture? Check out our GitHub and explore the code.

  • Building Amazon Capital Protection Intelligence: A Technical Deep Dive

    As a developer, I’ve always been fascinated by the complexities of Amazon e-commerce. In this article, I’ll take you on a technical journey of how we built our Amazon Capital Protection Intelligence, a solution that empowers sellers with data-backed strategy.

    Our solution uses a combination of n8n, Vector DBs, and Webhooks to process and analyze large datasets in real-time. The ‘Brand Moats’ detection algorithm is a key component of our solution, which identifies unwinnable fights for beginners. We also developed a ‘Safe Buy Price’ and ‘Strategic Entry Risk’ assessment module, which ensures investment decisions are backed by data, not hope.

    Our AWS Mumbai infrastructure provides a scalable and secure platform for our solution to operate. If you’re interested in learning more about our technical approach, click here to visit our website and explore our technical blog.

    Stay tuned for more technical deep dives and insights into our Amazon e-commerce solutions.

  • Building a Scalable Digital Spine with Custom n8n Workflows

    Hey fellow developers! Are you tired of building custom integrations for your clients only to have them break down under the weight of high-volume data transfers? I faced this challenge when building a custom workflow for a client, and I knew I had to find a better solution.

    That’s when I discovered n8n, a powerful workflow automation tool that can handle high-volume data transfers with ease. I built a custom n8n workflow that automated the client’s data transfers, and the results were incredible.

    With n8n, I was able to create a scalable digital spine for the client’s business, reducing manual data transfers and increasing data accuracy. And the best part? The workflow was built on a stable Debian 12 production environment, ensuring that it would run smoothly even under heavy loads.

    Check out our Custom Build Services and learn how we can help you build a scalable digital spine for your business.

    Ready to take your workflow automation to the next level? Contact us today to schedule a consultation and let’s get started on building your custom n8n workflow.

  • Building a 24/7 Digital Receptionist with n8n and Vector DBs

    I recently built a 24/7 digital receptionist using n8n and Vector DBs. The goal was to create a system that could answer calls instantly, identify the caller’s needs, and log everything while my team is away. Here’s a high-level overview of the architecture:

    Webhooks: I used webhooks to receive incoming call data from our phone system. The webhook sends a JSON payload to n8n, which triggers the workflow.

    n8n: n8n is the workflow engine that runs the logic for answering calls and identifying the caller’s needs. I used a combination of JSON and Vector DBs to store and retrieve caller data.

    Vector DBs: Vector DBs are a type of NoSQL database that allows for fast and efficient storage and retrieval of caller data. I used Vector DBs to store caller information, such as name, phone number, and reason for calling.

    By leveraging n8n and Vector DBs, I was able to build a robust and scalable system that can handle a high volume of calls. If you’re interested in building a similar system, I’d be happy to share more details.

    Check out our AI Voicebot solution for more information on how we can help you build a 24/7 digital receptionist.

    #ShahiRaj #n8n #VectorDBs

  • Building a 24/7 Digital Gatekeeper with n8n and Vector DBs

    I recently worked on a project that involved building a digital gatekeeper using n8n and Vector DBs. The goal was to automate the qualification process for website visitors and empower the sales team to focus on high-quality leads. Here’s a high-level overview of the architecture:

    1. n8n workflow captures intent, budget, and contact info from website visitors.
    2. Vector DBs store the qualified leads and sync with the AWS Mumbai database.
    3. The sales team receives only ‘hot’ leads, ensuring they can focus on closing deals.

    The result was a significant reduction in lead leakage and an increase in conversion rates. By automating the front-line qualification, we empowered the sales team to do what they do best – close deals. Get in touch if you’d like to learn more about this project and how we can help you build your own 24/7 digital gatekeeper.

  • My AI-Driven Photography Adventure with ProductStudioAI

    Hey developers! I just had the chance to play with the latest AI-powered photography tool from Shahi Raj, ProductStudioAI. I was blown away by how easy it was to generate 8 distinct, pro-grade scenes for my product, including a transparent PNG for my website.

    The process was seamless – I just sent one photo to ProductStudioAI and waited for the magic to happen. The result? A full gallery on Google Drive with SEO-ready names, all for just ₹100 per product. It’s like having a professional photographer on demand!

    I’m excited to see how this tool will transform my product catalog and boost my sales. If you’re a D2C seller looking to elevate your brand’s aesthetic without breaking the bank, give ProductStudioAI a try. DM ‘STUDIO’ and get your 8 pro shots in under 3 minutes.

    ProductStudioAI is the perfect solution for developers who want to take their product photography to the next level. Trust me, you won’t be disappointed!

    Tags: #ShahiRaj #ProductStudioAI #AIpoweredphotography #D2Cseller #Developer

  • 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.