in the beginning of 2025, we have already make some improvement to fonnte. we are adding features and changing some expected behaviour on fonnte.

Delay

Delay now starts on first target. previously, delay only works on multiple target. this is, while good to force single target to immediately sent and prevent any delay, this behaviour is not expected by most of our user. so we have changed the delay behaviour to delay each target, regardless the number of target.

Flow

We are adding flow to make chabot building easier. this is actually same as autoreply, chaining and submission but visually. even better, you can combine them all if you need them.

also, AI only supported via flow

AI setting

if you are using AI, you can set the AI to have their own behaviour.

AI data

Fonnte allow your AI to use your own data. using this data, your AI will act like personal assistant for your knowledgebase.

Response Source

We have added response source in the device->edit. we have now 3 response source. you can choose response from autoreply, spreadsheet, or flow.

spreadsheet still can only be used on regular plan and above it.

we are not planning to deprecate autoreply, chaining, and submission, or at least not yet.

but using flow is much greater and easier due to it's visual interface.

we encourage to build autoreply from flow.

Order

We also make order easier by adding custom duration and lifetime order for AI quota and AI data.

you can now order for 3 months or any month/year, all based on your needs.

Spreadsheet

for many end users, using variable like 081|admin|fonnte indeed helps a lot. but it has limitation.

we are adding spreadsheet to the rescue. it's as easy as excel.

this spreadsheet removing the needs of predefined variables in fonnte, like name,var1,var2 etc.

you can use your own variable name.

but still, you need 1 variable named "whatsapp" for target number.

for other names, it's up to you.

Server optimization

Our server also now have been optimized even more to handle more request and more dependable.

Flow is a "must have" feature in no code chatbot building.

fonnte already have several features like autoreply, chaining, and submission before but it's hard to visualize.

it also has it's own limitation.

so it's finally the time to move it all to flow.

Flow interface

all items are categorized in message, response, logic, import and action.

you can drag and drop an item in the menu to make an element.

then, you can link them to make the flow.

you can also clear the flow to reset all flow.

the save button is to save your flow.

everytime you save the flow will reset all path on your existing chats.

so all user that currently having chat with your chatbot will have to start over.

Setup

All package is eligible for using flow, even free one without limit.

To activate the flow, you need to edit your device :

1. Autoread must on
2. response source is flow

that's it.

you're good to go.

By default, AI do not use chat history.

every incoming chat is a new chat.

so it will behave differently than chatgpt and doesn't remember past conversation.

to enable history, you need to make a loop in the flow setting.

create 2 ai and 2 response, then link them circular.

example : ai 1 -> response 1 -> ai 2 -> response 2 -> ai 1.

it's easier to show an image

by using this flow, your ai will remember history and can answer better.

When adding your own data, sometime you'll face a problem where your ai answer is not based on desired data.

This is typically happen when your data is related each other, but highly similar.

for example, one data about register, one data about login, one data about reset password.

sometime the ai score chooses "login" data when the actual chat is about "cannot login".

therefore, "reset password" data is the actual data you expect to have highest score.

let's dig deeper.

Short vs long data

using previous case, why would i need to separate them to 3 data?

i can merge them and use 1 data instead!

yes, this is one of the correct approach.

with longer data, it means broader data range.

it's reserving overall topic, so you should not worry too much.

but still, if you still have another data that having similar topic, the problem will still exist.

this solution will only works, if you combine all related content as one data.

but, this also raise another issue, your cost will possibly increase.

so the second solution is to cut it to super specific short data.

only around 200-500 characters.

the data must super specific and not overlapping another data.

for example, "register","login","reset password".

this share common topic : account.

therefore, you need to rephrase your data to be very specific to each data about "register","login" and "reset password".

Long	Short
+ Keep the context	- separate context
+ easily do comparation and get related data	- cannot do comparation and related data is hard to get
+ easier to maintain	- harder to maintain
- less precise	+ more precise
- cost more	+ cost less
- slower response	+ faster response

When short data are good:

• Sensitive content where correctness is important.
• Scenarios where the answer needs to be very specific
• focused chat that only need a very specific part of the information.

example : register, login, reset password

When long data are good:

• Your data need to be related each other eventhough the subdata/section is different.
• Topics that require a lot of context for accuracy each other.
• Comparation or global data where subdata is meaningless without it (like "What are the differences between X and Y? or all api parameter data").

example : pricing, api documentation, step by step data

Add description & category

after cut the data short, you can also add some addition information and categorize it.

with this action, your data will obtain additional context and the ai would understand better.

inside the data, you can also add some keyword related to the data.

for example : Instead of "our lite plan," use "our lite plan includes API and webhook support.

do avoid ambiguity inside the data.

avoid "all plans have basic feature", instead use : "all plans include API and webhook support".

Add example

You can also add more example to it so AI can enhance it based on your example model.

for example in the documentation, fonnte offer some example in PHP.

this can be included as example.

other thing is add incoming message example.

so you can add something like :
question example : "how to order?","how much is ai quota price?"

Conclusion

we cannot ask ai to always correctly use specific data from our collection of data.

ai works using the power of statistic, which means it's all about probability.

what can we do is increase the probability by using known best practice above and let the statistic works as is.

After adding your own data and having ai quota, now you think about how it works.

let's made up a scenario where you have 3 data, each is around 1.500 characters length.

every data have their own score.

When you add any data, fonnte under the hood is generating and saving it's score.

around 1.500 characters on your data cost 1 ai quota.

Incoming chat process & cost

when a chat is coming, fonnte will give it a score, then compare it with all of your data's score.

the highest score relative to the question will be choosen.

but the data then will once again compared to the current chat and previous chat history.

it will compared once again with complete chats history.

then we have another highest score data.

after that, we will compare both highest data.

if they're not equal, then both of them is relevant to the chat and necessary to answer the question.

so the cost now is not just 1, but 2 due to additional data.

if the data is short enough and the total is less than 2000-2500 characters, your cost will more likely to be just 1.

but 2 might not the final cost you'll be charged.

there is also "hidden" cost that may occur due to your ai behaviour.

you may use chat history to make the chat flow is smooth, more like chatgpt behaviour.

this behaviour cost you more, can be around 1-2 additional ai quota depend on the chat history length.

if you do not use history, your ai might not remember previous chat, so it will behave like new chat.

this behaviour will not add cost for incoming data and the final incoming cost more likely to be 2 at most of the case.

Outgoing chat & cost

for response length, typically it will cost just 1.

but it the response is too long, it might get 2 or 3.

as long as we tried during development, most of our response cost 1 ai quota and rarely got 2.

it's including our lengthly code generation for our api example.

your outgoing chat cost will more likely to be 1 at most of the case.

Conclusion

so, in the end, your total cost is typically 2-3 ai quota.

from the incoming cost is typically 1-2 a quota.

while the outgoung cost is typically 1 quota.

but still, might go up to 5 ai quota due to 1-4 incoming data, and 1 outgoing data.

ai data is a menu to add more information to your ai.

this is useful to add your own data so ai can use this data to respond to your user.

this data has maximum 10.000 characters each.

Calculation

To add data, you will need data allowance.

as a start, every device will have 3 allowance.

you can delete/edit old data and create new data.

for 2.000 - 2.500 characters, it will be using 1 ai quota when used.

if your data around 8.000-10.000 characters, everytime this data is used, you will be cost al least 4 ai quota.

the more characters you have, the more expensive it is to be used.

to be able to send ai message, you need ai quota.

the ai quota can be ordered through order menu.

this ai quota have no expiration date.

as long as your device exist, the ai quota will also exist unless depleted due to be used.

Calculation

the ai quota will be calculated twice :

• incoming chat data
• outgoing chat response

so basically you will need at least 2 ai quota per chat.

why is at least? will it cost more than 2 per chat?

yes, it's all based on your data length and response length.

so in a typical chat, 1000 ai quota can be used to generate up to 500 chats

having ai indeed can help adding productivity.

currently ai is used only for chatbot.

you can use this ai feature with the help of flow menu.

by creating the flow, your ai is ready to be used.

Requirement

You will need quota ai to use this ai feature.

everytime you send an ai reply, your quota ai will be deducted.

you can also use your own data set you can add in the ai data menu.

with your own data, your ai will be personalized to your needs

Setup

To use this ai, it's pretty straightforward.

you can go to flow menu, then create the flow and use ai as reply.

your ai will use your own data (if any) to response to the chat.

Fonnte is does not wish to store any of your data, literally.

So, fonnte delete your data, regularly.

As per this documentation is written, these are the list and the lifecycle of how long will they stored on fonnte.

This API is used to delete a message via API.

You can delete the requested message you don't want to proceed anymore or other reason EXCEPT message with status processing.

processing message cannot be deleted.

if you want to delete it, you have to disconnect your device first, the processing message will changed to pending.

This way you can delete it.

<?php

$curl = curl_init();

curl_setopt_array($curl, array(
  CURLOPT_URL => 'https://api.fonnte.com/delete-message',
  CURLOPT_RETURNTRANSFER => true,
  CURLOPT_ENCODING => '',
  CURLOPT_MAXREDIRS => 10,
  CURLOPT_TIMEOUT => 0,
  CURLOPT_FOLLOWLOCATION => true,
  CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
  CURLOPT_CUSTOMREQUEST => 'POST',
  CURLOPT_POSTFIELDS => array('id' => ''),
  CURLOPT_HTTPHEADER => array(
    'Authorization: TOKEN'
  ),
));

$response = curl_exec($curl);

curl_close($curl);
echo $response;

If you prefer to see on postman, see here.

The token is device token. see how to get token.

Response

Successfull response

{
    "detail": "message 1 successfully deleted",
    "status": true
}

- invalid device : invalid token

{
    "reason": "invalid token",
    "status": false
}

- invalid message id : the message id does not exist or does not belong to your device.

{
    "reason": "invalid message id",
    "status": false
}

- cannot delete message with status processing : the message is being processed. message cannot be deleted

{
    "reason": "cannot delete message with status processing",
    "status": false
}