Blog

  • The Tech Requirements for Meta Verification.

    Getting the Green Tick isn’t luck; it’s data. To ensure a smooth verification process, you’ll need to meet the following technical requirements:

    • Domain Verification (DNS TXT records)
    • Business Manager 2FA
    • Display Name compliance

    These requirements may seem daunting, but we automate the check to ensure that you’re meeting all the necessary criteria.

    Our technical expertise will help you navigate the complex world of Meta verification and get your Green Tick in no time.

  • Anatomy of a Ban: How WhatsApp Detects Unofficial Tools

    Unofficial tools use ‘Headless Chrome’ to simulate a human, but WhatsApp’s AI detects the typing speed and session headers. In contrast, the Official Cloud API (used by Chatore) sends data directly to Meta’s servers, allowing for scale without risking a ban. Read more about the technical differences between unofficial and official tools.

  • PDF Generation on the Fly: HTML to PDF in n8n

    Generating dynamic invoices is easier than you think. I use an n8n node to inject variables (Client Name, Amount, Date) into a simple HTML template, convert it to binary (PDF), and attach it to a Gmail node. No QuickBooks needed. Check out this example workflow and learn how to automate your invoicing process.

  • Date-Math in n8n: Building a “Recurring” Workflow.

    I’ll demonstrate the logic behind our Patient Recall System: Query Database -> Filter Last_Visit < Today - 180 Days -> Check Next_Appointment is Empty -> Trigger WhatsApp Template It runs daily at 9 AM. A simple loop that ensures patient retention.

    The key to success lies in automating the workflow. With n8n and a bit of date-math, you can build a recurring workflow that boosts patient retention and recovers lost revenue. Check out Shahi Raj’s technical blog

  • Automating Outbound Campaigns: Google Sheets to Exotel

    I’ll share the workflow: n8n watches a Google Sheet column ‘Status’. If it changes to ‘Call Now’, it triggers an Exotel API call. The AI speaks the script, listens for the user’s reply, and writes the result back to the Sheet. A full loop, zero hands.

    This workflow automates outbound campaigns, reducing manual labor and increasing efficiency. By integrating n8n, Google Sheets, and Exotel, we’ve created a seamless process that streamlines communication with clients.

    Want to learn more about this workflow? Check out our blog post on automating outbound campaigns and discover how to boost your productivity.

  • Voice-to-JSON: Structuring Unstructured Audio.

    When it comes to transcribing audio recordings, manual listening is a slow and laborious process. I’ve developed a solution using OpenAI Whisper to quickly transcribe audio and an LLM to extract key fields like Name, Budget, and Urgency into a clean JSON object. This data is then pushed instantly to our CRM before the phone even hangs up.

    This process has significantly reduced the time spent on data entry and has improved the accuracy of our lead data. By automating this process, we’ve been able to make data-driven decisions and optimize our sales strategy. If you’re looking to streamline your sales process and improve your data accuracy, consider implementing a similar solution. Learn more about how we can help you achieve your sales goals.

  • The ‘Busy Tone’ is a Software Bug: Fix it with Exotel + n8n

    A physical phone line can only handle one call. A SIP trunk can handle thousands. I’ll show how I connect Exotel to n8n to spin up a new AI instance for every single incoming call, ensuring zero latency and zero waiting time.

    The ‘busy tone’ is not just a physical limitation, but a software bug that can be fixed. By leveraging Exotel and n8n, you can create an infinite capacity system that never says ‘busy’. Learn more about how ShahiRaj can help you solve this software bug.

  • Building a Quranic Vector Store: RAG for Scripture

    As a developer, I’ve always been fascinated by the challenges of searching for concepts in the Quran. Standard SQL search just doesn’t cut it, especially when it comes to understanding the semantic intent behind a user’s query.

    That’s why I decided to build a Quranic Vector Store using OpenAI Embeddings and a Vector Database. This allows the Digital Hafiz bot to understand the context and sentiment behind the user’s query, mapping their emotion to the relevant divine guidance.

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

    • Indexed the Quran using OpenAI Embeddings
    • Stored the embeddings in a Vector Database
    • Used a neural network to map the user’s query to the relevant embeddings
    • Retrieved the most relevant Ayats from the Vector Database

    By using this approach, the Digital Hafiz bot can provide a more personalized and meaningful experience for users, helping them to deepen their understanding of Islam and live a more meaningful life.

    Try the Digital Hafiz today and experience the power of Vector Search for yourself!

    #ShahiRaj #DigitalHafiz #QuranSearch #VectorSearch

  • Linking the Misri Calendar to n8n Triggers: A Technical Deep Dive

    As a developer, I’m always on the lookout for innovative solutions to real-world problems. The AlQuranAlKareembot’s ‘Miqaat’ automation feature sparked my interest, and I decided to dig deeper into its technical aspects.

    One of the key challenges I faced was linking the Misri Calendar to n8n triggers. The Gregorian scheduler simply doesn’t work for Hijri dates, making it essential to create a custom solution.

    I developed a ‘Miqaat Node’ – a custom Javascript function that checks the current date against the Misri Calendar algorithm. If the day matches Friday Eve, it triggers the specific Surah Kahf workflow.

    If you’re interested in exploring more technical aspects of the AlQuranAlKareembot, I encourage you to join the conversation and share your thoughts!

  • Regex for Finance: Parsing Text Commands in n8n

    I’ve been working on a project to automate expense tracking using n8n, a workflow automation tool. One of the key features is parsing text commands from Telegram messages.

    The text command might look like this: ‘Paid 2000 for server hosting’. My goal is to extract the amount, category, and narrative from this text and push it to Firestore/Sheets.

    I’ll break down the JavaScript Regex logic I use to achieve this. If you’re interested in learning more about regex and how to apply it to finance, stay tuned for the next part of this series.

    Check out the ShahiRaj blog for more technical articles on finance and workflow automation.

    #ShahiRaj #n8n #Regex