Intelligent Text Parsing – Day 3: Final Touches & Wrap-Up
Welcome to Day 3 of our No-Code Workshop!
By now, you already have a fully functional AI-powered parser that receives messages from Telegram, extracts structured information using NeurochainAI IaaS, and responds instantly, all built with n8n.
Today, we’ll walk through the final steps to test, polish, and validate your workflow for real-world usage.
Step 1 – Test Your Parser
Go to your Telegram bot and send a few different messages.
Example:
“Hi, my name is Julia, I’m 27 and my number is (11) 91234-5678.”
If your Set node includes:
- Name: The full name
- Age: The age in numbers only
- Phone: The phone number with only digits
Then your bot should reply with something like:
Name: Julia
Age: 27
Phone: 11912345678
Test with:
- Different message formats
- Missing or incomplete information
- Extra details the parser should ignore
Step 2 – Adjust Descriptions in the Set Node
If something didn’t extract the way you expected, try tweaking the Value (description) in your Set node.
For example:
Field Name
Value
A valid email address only, with no extra text
Address
The full street address, including number and city
Date
The appointment date in DD/MM/YYYY format if available
Remember: the better the instruction, the better the AI output.
Step 3 – Organize Your Supabase Table (Optional)
If you're storing the extracted data in Supabase, review your table:
- Are all the fields mapped correctly?
- Do the column types match the data?
- Do you want to add timestamps?
Supabase makes it easy to analyze, export, or connect your data to dashboards later.
Step 4 – Ideas to Expand Your AI Parser
Now that your base workflow is working, here are a few things you could add:
- ✨ Format responses with Markdown or emojis for friendlier UX
- 🗃️ Add logs or tracking via a second Supabase table
- 📧 Trigger email or webhook notifications based on extracted data
- 🌍 Translate fields before saving using another AI step
Final Thoughts
You now have a flexible, powerful AI parser that can:
- Extract anything you define
- Understand natural language
- Work with any user input
- Scale with new use cases
All of this using NeurochainAI IaaS and n8n, with no code.
Share What You Built!
If you found this useful or adapted it for something cool (like support tickets, lead capture, bookings, or feedback forms), share your build with the community!
Tag us or reach out, we’d love to see what you’re creating.
And stay tuned for more workshops coming soon. 🚀