🆕AI Node

AI that decodes every message and powers seamless omnichannel actions.

The AI Node is the intelligence engine inside iSlash AI’s AI Agents. It uses advanced LLMs to instantly understand any customer message, then proceeds extracting key information, identifying intent, making decisions, and structuring data in real time.

It works across all supported channels, including:

• WhatsApp

• Facebook Messenger

• Instagram DM

• WeChat

• Website Plugin Chat

Every processed result is saved as a variable, enabling lightning-fast, intelligent responses that keep customers engaged and moving forward.

Smart Understanding That Feels Human

By interpreting intent, extracting details, and understanding context, the AI provides responses that feel personalized and relevant. Leads feel heard and guided, not pushed through a rigid script.

When a customer sends a message on any channel, the AI Node will:

1

Receive the customer’s input

Capturing customer's messages from WhatsApp, Messenger, Instagram, WeChat, or your website chat.

2

Process the text using an LLM

The AI analyzes the message using top-tier LLMs like ChatGPT-4o and Google Gemini 1.5 (with optional Knowledge Base)

3

Generate a specific output

You get a structured, strict, and traceable result.

4

Save the output as a variable

This variable becomes reusable intelligence that travels with the customer throughout their entire interaction.

5

Power real applications that move leads forward

Use the variable instantly to:

• Personalize replies

• Trigger conditional routing

• Segment customers

• Drive different logic paths inside your AI Agent

Every lead receives instant replies that prevent drop-offs, smart and relevant responses that feel human, and frictionless interactions that guide them seamlessly toward the next step. This turns iSlash AI into a dynamic, intelligent automation engine, all and no coding required.

When to Use AI Node

Below are detailed scenarios with clear steps describing how the AI Node works inside the actual flow.

Scenario: Clean or transform customer messages

Use Case: Marketing team wants clean answers from customers, even if they reply with typos or slang.

How It Works in the automation:

1. Customer sends a typo-heavy reply:

   “i wan the promo code pls ty”

2. AI Node rewrites

   • Question: “Rewrite the message into proper English.”

   • System Prompt: “Do not change meaning. Keep it simple.”

3. Output: “I want the promo code, please.”

4. Save output as variable: clean_message_1

5. Variable used for:

   • Reply to customer: “Just to confirm, you said: {{clean_message_1}}”

   • Use for keyword tagging (e.g., promo, request)

   • Analyze customer behaviour

   • Use in future automated responses

Build this AI Agent to clean or transform customer's message by following this step-by-step guide.

Scenario : Keyword / Phrase Detection Using AI

Use Case: Detect if customer asks about business hours — no matter how they phrase it.

How It Works in the automation:

1. Customer message: “What time do you guys open?”

2. AI Node identifies the intent

   • Question: “Is this message asking about opening hours? Answer YES or NO.”

   • System Prompt: “Only output YES or NO.”

3. Output: “YES”

4. Variable: ask_business_hours

5. Variable usage:

   • If YES → send automated hours

   • If NO → continue to FAQ

   • Label as “Operating Hours Enquiry”

Scenario : Language Detection or Auto-Translation

Use Case: You want to know what language the customer uses and auto-respond accordingly.

How It Works in the Flow:

1. Customer message: “你好，我想预约。”

2. AI Node detects language

   • Question: “Detect the language of the message. Return only the ISO code (e.g., EN, ZH, MS).”

   • System Prompt: “Only output the ISO language code.”

3. Output: “ZH”

4. Variable: language_code

5. Variable usage:

   • If ZH → reply in Chinese

   • If EN → reply in English

   • Add label for segmentation (language-based marketing)

Scenario : Identify the Customer’s Pricing Enquiry Intent

Use Case: A business wants to automatically detect whether the customer is asking about pricing and route them accordingly.

How It Works in the Flow:

1. Customer message: “Hi, can you tell me how much lash lift costs?”

2. AI Node processes the message

   • Question: “Determine if the customer is asking about pricing. Answer YES or NO only.”

   • System Prompt: “You are a strict classifier. Only output YES or NO. No explanations.”

3. Output: “YES”

4. Save output as variable: intent_pricing

5. Variable usage:

   1. Condition: IF intent_pricing = YES → send price list IF intent_pricing = NO → continue normal flow

   2. Segment as “Price Enquiry Lead”

   3. Trigger a follow-up sequence

Build this AI Agent by following this step-by-step guide.

More completed conversations. Stronger customer intent. Higher conversion rates.

The AI Node brings advanced LLM processing into iSlash AI’s omnichannel AI Agents, enabling every customer message to be understood, analyzed, and acted on instantly.

It extracts clean information, identifies intent, makes decisions, and guides each customer down the right path, across WhatsApp, Facebook Messenger, Instagram DM, WeChat, and Website Chat.

With this, businesses can deliver automation that is:

• More personalized

• More efficient

• More scalable

• Truly accurate.

Supporting use cases across:

• Customer service

• Sales & promotions

• Bookings & appointments

• Support workflows

• Lead qualification

• CRM enrichment

All without writing a single line of code.

Start building AI Agent now:

AI Node | iSlash AI User Guide & Setup Documentationislash.io

AI Agents is available on all paid plans, start building your AI Agents for conversions now:

iSlashapp.islash.io