Blog

I’ve been experimenting with building an AI Personal Assistant Bot on Telegram/WhatsApp, and the results have been incredible. By leveraging Debian 12 as the underlying OS, I’ve been able to create a seamless experience for users.

The bot captures ‘random’ weekend ideas, organizes Monday priorities, and tracks spends in real-time, all while running silently in the background.

My goal was to empower users to be present with their families while the digital assistant takes care of administrative tasks. With this bot, I’ve achieved just that.

By focusing on automation and streamlining administrative tasks, I’ve been able to create a truly unique experience for users. Want to see how I built this? Check out the code or DM ‘ASSIST’ for more info.

I recently worked on a project to build a Custom RAG AI Agent that acts as a digital archive assistant for companies. The goal was to create a system that could search through a large amount of private company data, hosted securely on AWS Mumbai, and provide instant answers to team members.

The tech stack involved using n8n for workflow automation, Vector DBs for efficient data storage, and Webhooks for seamless integration. The AI agent was trained to read and understand the context of various documents, making it a valuable tool for research and decision-making.

One of the key challenges was ensuring the security and integrity of the data. We used AWS IAM roles to control access and ensure that only authorized team members could access the data.

With the ‘Digital Archive’ assistant, teams can now focus on high-priority tasks, knowing that their company data is always accessible and up-to-date.

Want to learn more about building your own Custom RAG AI Agent? Get in touch with our team.

As a developer, I’m always excited to talk about building solutions that make a real impact. Our AI Support Widget is one such solution that can transform your support team’s efficiency and performance.

By leveraging your own knowledge base and a secure Debian 12 setup, we can absorb 70% of routine queries instantly. This means that your human agents can focus on the complex, high-value customer issues that require their expertise.

So, how do we do it? We use a combination of n8n, Vector DBs, and Webhooks to create a seamless experience for both customers and support agents. Check out our tech stack

As a developer, I was tasked with building an AI Visiting Card Scanner that could read business cards and sync the data to a user’s Excel/CRM in under 3 seconds. Here’s a technical deep dive into the architecture and implementation of this project.

We used n8n as our workflow automation tool, Vector DB for our database, and Webhooks for communication between services.

The AI Visiting Card Scanner uses a combination of OCR (Optical Character Recognition) and machine learning algorithms to extract data from business cards. The extracted data is then sent to the user’s Excel/CRM via AWS Mumbai.

Want to learn more about the technical details of this project? Reach out to me and I’ll be happy to share more.

In this post, we’ll take a technical dive into the @MisriCalendarBot, exploring its architecture, APIs, and implementation details.

We’ll cover the following topics:

• The API integration with @MumineenORG for namaz timings
• The implementation of the Dawoodi Bohra Hijri calendar events
• The weather API integration for the latest forecast

By the end of this post, you’ll have a deeper understanding of the technical aspects of the @MisriCalendarBot.

I’m excited to share with you my latest project, the ‘Founder’s Freedom’ Assistant, an AI Personal Assistant Bot built using n8n, Vector DBs, and Webhooks.

The assistant is designed to run on our AWS Mumbai infrastructure and provides lifestyle assistance by organizing thoughts, tracking expenses, and setting priorities. The bot is built using a combination of AWS services and custom code, allowing for seamless integration and scalability.

I’ll be sharing more about the technical details of the project, including the architecture, code logic, and implementation results, in future posts. Stay tuned!

Learn more about the ‘Founder’s Freedom’ Assistant and how it can empower you to be 100% present with your family.

I recently worked on a project to build an AI Meeting Scheduler, which we’ve dubbed the ‘Friday Finish’ Assistant. This tool aims to prevent the back-and-forth ‘Are you free at 3 PM next Tuesday?’ scenario that often plagues Friday afternoons.

The solution leverages n8n, Vector DBs, and Webhooks to empower teams to share a link or trigger a WhatsApp message, which then checks real-time Google Calendar availability and secures the slot instantly. The AWS Mumbai server ensures seamless syncing and eliminates manual entry and double bookings.

Want to learn more about the technical details behind this project? Check out our GitHub repository and see how we’re pushing the boundaries of AI-powered productivity tools!

I recently worked on a project to build a real-time field data collector using ShahiRaj Data Collector, n8n, and Vector DBs. The goal was to empower field staff to log photos, locations, and site data in real-time, and make this data instantly available to management via a dashboard.

Here’s a high-level overview of the architecture: ShahiRaj Data Collector app collects data from the field, which is then forwarded to n8n via Webhooks. n8n processes the data and stores it in Vector DBs, which is then queried by our dashboard to provide real-time visibility.

Check out the code and architecture details for this project on our GitHub repository. #ShahiRaj #n8n #VectorDBs

I recently worked on building an AI Voicebot that acts as a high-speed assistant, answering calls instantly, qualifying the caller’s needs, and providing information 24/7. This project involved integrating Exotel with an AI-powered backend running on AWS Mumbai.

The solution uses a combination of natural language processing (NLP) and machine learning algorithms to understand the caller’s needs and respond accordingly. The backend is built using a microservices architecture, allowing for scalability and reliability.

One of the key challenges we faced was ensuring seamless integration between the AI-powered backend and the Exotel API. We achieved this by using Webhooks to trigger actions in real-time.

Now, let’s take a look at the tech stack used in this project:

• n8n as the workflow automation tool
• Vector DBs for storing caller information
• Webhooks for real-time communication between services

Check out the code repository and learn more about the technical details of this project.

Category: Developer Log

Tags: #ShahiRaj #AIVoicebot #TechnicalDeepDive #n8n

I’m excited to share the technical details behind our AI All-in-One Widget, the Multi-Channel Support Hub A8. This project was a thrilling challenge that required a deep understanding of AI, n8n, Vector DBs, and Webhooks.

At the core of the widget is a secure Debian 12 setup, which provides a robust foundation for our AI-powered support solution. We’ve integrated n8n to handle the workflow and Vector DBs to store the data. Webhooks enable seamless communication between platforms.

Explore the technical architecture behind the Multi-Channel Support Hub A8 and learn how we can help you build a similar solution for your business.