How to Set Up No Match Reply With AI in ZazzyAgent
A customer will eventually type something your predefined chatbot doesn't recognize.
Maybe your bot has a pricing flow, but the customer asks:
Do you offer discounts for annual plans?
No keyword matches.
Without a fallback, the customer may receive nothing useful.
ZazzyAgent provides No Match Reply for this situation.
What is No Match Reply?
No Match Reply is the response used when a customer's message doesn't match an existing predefined bot flow or trigger.
Instead of leaving the customer without an answer, you can configure a response.
That response can also use AI.
The current AI training workflow allows No Match Reply to use an AI Reply connected to the relevant trained knowledge.
Why does No Match matter?
Without it:
Customer
↓
Unknown message
↓
No match
↓
Nothing useful
With it:
Customer
↓
Unknown message
↓
No Match
↓
AI Reply
↓
Useful answer
No Match vs normal flow
A normal flow handles something you've deliberately configured.
For example:
pricing
→ Pricing flow.
No Match handles something that doesn't match.
For example:
Do you have a discount for startups?
Why use AI for No Match?
You don't know every way a customer will phrase a question.
A customer may ask:
How much?
Another:
What's the price?
Another:
Can you tell me the cost?
A keyword-based system might require several triggers.
An AI fallback can understand the question more naturally.
Before you configure it
You need:
AI knowledge/training
Useful business information
A configured AI Reply
A connected bot/channel
A test account
Step 1: Open the No Match configuration
Open the relevant bot settings in ZazzyAgent.
Find the No Match action/configuration.
This is the system-level fallback for unmatched customer messages.
Step 2: Open its Flow
The No Match action can be configured through Flow Builder.
Open the flow associated with No Match.
Step 3: Add AI Reply
Add or open the AI Reply component.
Connect it to the No Match path.
The current reference workflow specifically configures No Match by opening its flow and assigning the AI training campaign to the AI Reply component.
Step 4: Select the appropriate AI knowledge
Choose the AI training/knowledge configuration that should answer the customer's questions.
For example:
Customer Support Knowledge
rather than a sales-only knowledge source.
Step 5: Enable No Match
Return to the relevant bot configuration and enable No Match Reply.
Save the settings.
What happens now?
Suppose your existing bot recognizes:
pricing
booking
support
but a customer asks:
Do you offer a free trial?
If that isn't a predefined flow trigger, the No Match Reply can hand the question to AI.
No Match doesn't mean "AI knows everything"
This is important.
AI should answer using the Knowledge you provide.
If your Knowledge says nothing about free trials, the agent shouldn't invent one.
Tell AI what to do when information is missing
A useful instruction is:
If the answer isn't available in Knowledge, don't guess. Tell the customer you don't have the information and offer human assistance.
No Match and AI Agent are different approaches
No Match + AI Reply
AI acts when predefined automation doesn't match.
AI Agent for All Queries
AI handles the conversation broadly as the primary assistant.
Neither is automatically right for every business.
When No Match is useful
No Match is particularly useful for:
FAQ bots
Support bots
Structured menus
Lead-generation bots
Booking systems
Businesses with many predefined flows
Example: Support bot
Configured:
Track Order
Returns
Refunds
Contact Support
Customer asks:
How long does delivery normally take?
No predefined path matches.
AI fallback answers from Knowledge.
Example: Lead-generation bot
Configured:
Request Quote
Book Demo
Pricing
Customer asks:
Can you work with companies in Dubai?
No exact trigger.
AI answers from the business Knowledge.
No Match and human handoff
No Match can also be used as a safety net.
For example:
Unknown Question
↓
AI tries to answer
↓
Information available?
↙ ↘
Yes No
↓ ↓
Answer Human
This prevents the AI from making unsupported claims.
Configure a clear fallback
Your fallback shouldn't simply be:
I don't understand.
It should still help.
For example:
I can help with questions about our services, pricing and bookings. What would you like to know?
Or, when AI is connected:
Let me check that for you.
then let the AI answer.
No Match and AI context
The current AI configuration supports contextual memory, which can be useful when a customer's unmatched question depends on previous messages.
For example:
Customer:
Do you have the premium plan?
AI:
Yes.
Customer:
Is that available for teams?
The second question is difficult to understand without the previous context.
Test No Match deliberately
Don't test only your known keywords.
Send unusual questions.
Examples:
What is your refund policy?
Do you have annual billing?
Are you open Sunday?
Can I speak to a human?
I have a problem with something else.
Check the difference between "No Match" and "No Answer"
These aren't necessarily the same.
No Match
means the predefined trigger/path wasn't matched.
The AI may still be able to answer.
No Answer
means the AI itself may not have enough information.
Your fallback should account for both situations.
Common problems
No Match never fires
Check whether No Match is enabled.
No Match fires but AI doesn't respond
Check the AI Reply configuration and selected knowledge.
AI responds with incorrect information
Check your AI training/Knowledge.
AI replies to everything
You may have configured AI for all queries instead of fallback-only.
When should you use AI for No Match?
A strong default for many structured bots is:
Use predefined flows for important actions, and AI fallback for natural-language questions.
This gives you both control and flexibility.
Recommended architecture
Customer Message
↓
Matches predefined flow?
↙ ↘
Yes No
↓ ↓
Structured AI No Match
Flow ↓
↓
Knowledge available?
↙ ↘
Yes No
↓ ↓
Answer Human
This is one of the simplest ways to add AI to an existing chatbot without rebuilding the entire automation.