AI-Powered Order Processing and Order Refund Chatbot for Restaurants

Does your order and refund process take a long time? Do you often hear reviews from your customers about the waiting time for the service center being too high? Do you want to automate the ordering and refund process for your valuable customers to enhance their experience? SpringML has all the answers to the above queries. We built chatbots that are capable of placing orders and refunding the money.

Coffee Ordering Chatbot

A chatbot takes the orders and displays the total amount to be paid at the counter.

  1. Order a coffee with customizations stated by the customer: The chatbot can take custom orders like decaf, half cream, no sugar, etc.
  2. Order a coffee as per the bot’s recommendations: The chatbot will recommend popular drinks in the store.
  3. Order a coffee within a specific price range: The chatbot shows options within the price range given by the customer.

Solution Architecture

Coffee Ordering Chatbot Flow SpringML

Detailed Instructions/Runbook

  • Navigate to and create a Dialog Flow agent. A GCP account is required to create a Dialogflow agent
  • Create a Google Sheet API to store the order information
  • Responses to the Dialogflow intents are enabled using Dialog Flow fulfillment. The fulfillment makes a call to the Google Sheet and fetches the order details when a query is made by the end-user.
  • Currently, the bot accepts orders with customizations stated by the customer, orders as per the bot’s recommendations, and orders within a specific price range
  • Webhooks are triggered to send requests to Google sheet through the GCP cloud function. All the orders received from a customer are stored in Google Sheet using the Google Sheet API
  • Requests are made to the Sheet API to store and fetch details like order summary and total amount from Google Sheets

Watch the video to know more about our Coffee Ordering Chatbot by navigating our Video Resource,

Order Refund Chatbot

A chatbot can refund money under various circumstances mentioned below:

  1. Refund money due to late arrival of the order: A customer will receive a complete refund of the amount of an order delivered beyond the time guarantee window declared by the restaurant.
  2. Refund due to delivery of a wrong item: A partial or complete refund is processed if he has received a different item from what one has ordered.
  3. Refund due to missing items/ partial order: A customer is entitled to a refund or future credits to the account if one does not receive all the ordered items.
  4. Refund money/provide future credits due to unsatisfactory order: A customer is provided a refund or future credits if one is upset with the bad quality of the food, poor hygiene, inaccurate customizations, etc.

Solution Architecture

Order Refund Chatbot Flow SpringML

Detailed Instructions/Runbook

  • Navigate to and create a Dialog Flow agent. The GCP account is required to devise the DialogFlow agent
  • Utilizing Dialog Flow, establish the fulfillment responses to the Dialog Flow intent
  • Currently, the bot can refund money under certain circumstances like late arrival of an order, wrong item delivery, partial order delivery, and unsatisfactory order.
  • Once the chatbot is created using the Dialogflow framework, the next step is to integrate the bot with Twilio for connecting the user to a live agent
  • Navigate to “”, create an account in Twilio and get your mobile number verified. A free trial number is enabled that is used to test the phone calls. Copy the script obtained from Twilio and create a cloud function. Integrate that cloud function using a webhook call
  • To integrate the bot with the cloud function, we need to create a webhook and trigger it using a tag
  • After completing the Twilio integration, integrate it with the user interface for the image upload button in case a wrong item delivery scenario takes place

The chatbot/voice bot is integrated with the current customer database and contact center agencies like Mitel, Avaya, Genesys, Twilio, Cisco, etc. Chatbot utilizes the in-built sentiment analysis feature, and that data can be used to determine the need for bringing in a live agent.

Watch the video for more about our Order Refund Chatbot by navigating our Video Resource,


There are some limitations to the Dialogflow messenger. For example, the option to upload an image when the incorrect item is delivered is not available.

To overcome this problem, an existing user interface is utilized that includes the image upload functionality.

Thus, CCAI eliminates inefficiencies in the day-to-day operations of a restaurant and makes them smarter, quicker, and better. It creates a differentiated customer experience and strengthens the reputation built over generations. Artificial Intelligence along with other modern techniques has transformed the way we enjoy food.

For more details go through our solution overview here:

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