NeurochainAI No-Code: Intelligent Text Parsing
Last updated
Last updated
This guide teaches you how to build a fully functional AI-powered message parser using NeurochainAI IaaS and n8n, all without writing code. You’ll learn to read, classify, extract, and respond to natural language messages across any platform you connect to your automation, such as Telegram, webhooks, forms, CRMs, or databases.
Your automation will be capable of:
✅ Understanding user intent (e.g., booking, inquiry, registration) ✅ Extracting structured data (e.g., name, date, address, phone) ✅ Formatting and returning clean, readable responses ✅ (Optional) Saving structured data to Supabase or another backend
You can use this setup in:
Support bots
Lead forms
Booking systems
Feedback processors
Multi-channel inboxes
Host it on a VPS (like DigitalOcean, Hetzner) or use n8n cloud.
Deployment guide: How to
Generate an API Key for the model you'd like to use (e.g., Meta-Llama).
Set up a table to store structured data (e.g., name, date, phone)
Get your API credentials from Project Settings → API
Use Telegram, Forms, or Webhooks — this guide uses Telegram for illustration, but the setup works with any source.
Here’s the automation logic you’ll implement:
Trigger – A message is received (via Telegram, webhook, or form)
Field Definitions – You define what to extract (name, date, etc.)
Prompt Builder – Dynamically creates the AI prompt
AI Request – Sends the prompt to NeurochainAI
Response Handler – Returns a formatted response
(Optional) Database Insert – Stores the structured data in Supabase
Add a Telegram Trigger or Webhook Trigger.
This captures incoming messages from your users.
Step 2: Define Fields to Extract
Add a Set Node with key-value pairs:
Name
The full name of the user
Age
The age in numbers only
Phone
The phone number with only digits
A valid email address only, no extra text
Address
Full street address, including number
Paste this into a Code Node:
This makes your automation fully dynamic — update fields in the Set Node only.
Configure a HTTP Request node:
Method: POST
URL: https://ncmb.neurochain.io/tasks/message
Headers:
Authorization: Bearer YOUR_API_KEY
Content-Type: application/json
Body (JSON):
Use a Telegram Send Message or Webhook Response node to send the AI output back:
Text:
Chat ID:
Add a Supabase Insert node.
Map fields (e.g., Name
, Age
, Phone
) to columns in your table.
Use it to log data, generate dashboards, or sync to other systems.
Send test messages like:
"Hi, I’m Lucas, 25 years old. My phone is (11) 91234-5678."
Verify if it extracts:
Name: Lucas
Age: 25
Phone: 11912345678
Try:
Different sentence structures
Missing values
Extra irrelevant text
Adjust descriptions in the Set Node if needed.
💬 Add multiple language support using a translation API
📩 Trigger follow-up emails or WhatsApp messages
🧾 Log interactions in Google Sheets or CRMs
🎨 Format responses with Markdown, HTML, or emojis
🔁 Add logic for fallback replies or validation
You now have a flexible, real-time, no-code AI-powered parser that:
Understands natural language
Extracts structured data
Works across platforms (Telegram, Web, Forms, etc.)
Can respond, store, or act on the results
All powered by NeurochainAI IaaS and built with n8n, without touching a single line of backend code.
If you’ve adapted this workflow for bookings, support, lead gen, or something unique... show it off! Join the conversation in our community on Telegram or Discord, and inspire others with your automation.
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For Telegram: Set up a bot via , then paste the API token in the node.
🎁 Pre-configured with Telegram, AI prompt, and response nodes.