Chatbot Integrations – Adding an Integration in Teneo - DZone AI

If you want your chatbot to be able to know the answer to more than just the things you teach it about your business you can integrate to other services. Why invent the wheel twice? With integrations, you can have loads of information that might change from day to day without having to constantly update your solution manually.

Let’s look into how you add an integration in Teneo Studio.

To correctly handle an input of a user, a bot may need to connect to external services. For example, you may want to provide weather information or your bot may need to initiate a reset password process. In Teneo these calls to external services and the handling of their responses are carried out by Integrations. You add an integration to your solution once, after that it’s available for any flow in that solution.

In this example, we will create a flow that uses an integration that provides the number of calories in a coffee, like this:

User: How many calories in a flat white?

Bot: One flat white contains about 223 calories, a walk of about 56 minutes should be enough to burn them.

To make this possible, we are first going to set up an integration and then create a flow that makes use of the integration. The final result will look like this:

Set up the Nutrition Integration

First, we’re going to set up the integration. These are the steps to add an integration in Teneo:

Open the ‘Solution’ tab in the solution’s main window and select ‘Resources’ in the purple bar on the left hand side
Select ‘Integration’ at the top
Click the ‘Add’ button to create an integration
Name the integration Nutrition
Click the ‘back button’ in the top left to leave the integration’s backstage view so that you enter the main integration view

Set up a Method

An integration can contain multiple methods. A method is a block of code which only runs when it is called. You can pass data into the method and after executing the code, the method return the results. Here we want to create a method that returns the calories and walking duration to burn these calories for the coffee drink that was passed into the method.

When you created the integration, a ‘Default Method’ was automatically created. Let’s give it a proper name and add an input parameter we will use to pass data into the method and add two output parameters that we will use to return the results:

Re-name the method by replacing ‘Default Method’ in the ‘Name’ field with Get calories and add the description Returns calories for a given drink and the walking duration required
to burn the calories.
On the right, click on the ‘Inputs’ and the ’Outputs’ tab to see the input and output parameters (if not yet visible already).
Click ‘Add’ in the input parameters panel to add a new input parameter (for the coffee to find the calories for) and give it a name and a description:

Name the input parameter query.
Add the description: The coffee drink to find the calories for. For example: 'cappuccino'
or 'espresso'.

Now let’s add an output parameter for the calories found. Click ‘Add’ in the output parameters panel and name it as follows:

Name: calories.
Description: The calories found.

Finally, add the last output parameter for the walking duration:

Name: walkingDuration.
Description Walk duration in minutes to burn the calories.

Add the Script to the Method

To complete the method, let’s add the script which will be executed when the integration is called by the flow and save the method:

#integration #machine learning #chatbot #rpa #chatbot development #conversational ai #ai artificial intelligence #ai chatbots #cpaas

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Chatbot Integrations – Adding an Integration in Teneo - DZone AI

Erwin Boyer

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How This AI-Enabled Chatbot Radically Transformed Cancer Care Amid Pandemic

The critical industry that has been massively impacted by the pandemic is the healthcare sector; however, AI’s involvement has helped the industry weather the pandemic storm. The AI applications by companies bring back patients’ lives from the edge and improve diagnostics and treatment and help healthcare providers make informed decisions quickly. One such application has been developed by Hospido, India’s first holistic cancer care platform with which cancer patients can get the right treatment advice from India’s best cancer doctors, without visiting hospitals amid pandemic.

The pandemic lockdown has forced many people, including cancer patients, to avoid hospitals and discontinue their treatment due to coronavirus risk. And this is what triggered Karan Chopra, the founder of Hospido to bring out quality healthcare to these cancer patients through telemedicine and satellite treatments centres for providing the right treatment at the right time. In this article, Analytics India Magazine, got in touch with him to understand how this startup revolutionised cancer carer amid pandemic.

#startups #ai chatbot #ai chatbot transformed cancer care #ai-enabled chatbot #chatbot #chatbot ai #chatbot for pandemic #chatbot india #chatbot transformed cancer care #hospido startup

Meggie Flatley

1594306440

Chatbot Integrations – Adding an Integration in Teneo - DZone AI

If you want your chatbot to be able to know the answer to more than just the things you teach it about your business you can integrate to other services. Why invent the wheel twice? With integrations, you can have loads of information that might change from day to day without having to constantly update your solution manually.

Let’s look into how you add an integration in Teneo Studio.

To correctly handle an input of a user, a bot may need to connect to external services. For example, you may want to provide weather information or your bot may need to initiate a reset password process. In Teneo these calls to external services and the handling of their responses are carried out by Integrations. You add an integration to your solution once, after that it’s available for any flow in that solution.

In this example, we will create a flow that uses an integration that provides the number of calories in a coffee, like this:

User: How many calories in a flat white?

Bot: One flat white contains about 223 calories, a walk of about 56 minutes should be enough to burn them.

To make this possible, we are first going to set up an integration and then create a flow that makes use of the integration. The final result will look like this:

Set up the Nutrition Integration

First, we’re going to set up the integration. These are the steps to add an integration in Teneo:

Open the ‘Solution’ tab in the solution’s main window and select ‘Resources’ in the purple bar on the left hand side
Select ‘Integration’ at the top
Click the ‘Add’ button to create an integration
Name the integration Nutrition
Click the ‘back button’ in the top left to leave the integration’s backstage view so that you enter the main integration view

Set up a Method

An integration can contain multiple methods. A method is a block of code which only runs when it is called. You can pass data into the method and after executing the code, the method return the results. Here we want to create a method that returns the calories and walking duration to burn these calories for the coffee drink that was passed into the method.

When you created the integration, a ‘Default Method’ was automatically created. Let’s give it a proper name and add an input parameter we will use to pass data into the method and add two output parameters that we will use to return the results:

Re-name the method by replacing ‘Default Method’ in the ‘Name’ field with Get calories and add the description Returns calories for a given drink and the walking duration required
to burn the calories.
On the right, click on the ‘Inputs’ and the ’Outputs’ tab to see the input and output parameters (if not yet visible already).
Click ‘Add’ in the input parameters panel to add a new input parameter (for the coffee to find the calories for) and give it a name and a description:

Name the input parameter query.
Add the description: The coffee drink to find the calories for. For example: 'cappuccino'
or 'espresso'.

Now let’s add an output parameter for the calories found. Click ‘Add’ in the output parameters panel and name it as follows:

Name: calories.
Description: The calories found.

Finally, add the last output parameter for the walking duration:

Name: walkingDuration.
Description Walk duration in minutes to burn the calories.

Add the Script to the Method

To complete the method, let’s add the script which will be executed when the integration is called by the flow and save the method:

#integration #machine learning #chatbot #rpa #chatbot development #conversational ai #ai artificial intelligence #ai chatbots #cpaas

Erwin Boyer

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AI Chatbots for Business: Why You Need One Now!

It’s said that Artificial Intelligence will be just as smart as humans by 2050. Experts like Ray Kurzweil have even predicted that we’ll achieve a technological singularity by 2045.

From that point on, it’s believed that AI will start inventing Nobel Prize-winning inventions every 5 minutes. Granted it’s gonna be out of our control, but hey, at least we’ll see a revolutionary breakthrough.

We may think that these claims are outlandish and ridiculous, but if someone were to tell me in the 70s that there will be self-driving cars in the future, I would’ve wanted to smoke whatever they were smoking.

But guess what, here we are in 2020, and Tesla already has their self-driving cars on the roads right now. And these were all recently developed technologies. Did you know that the first chatbot was actually launched in 1966?

Features of AI Chatbots

Why Do You Need an AI Chatbot?

Chatbots Across Various Industries

Wrapping Up

#ai-chatbot #what-is-a-chatbot #chatbot-online #chatbot #chatbot-website #facebook-chatbot #google-chatbot #best-chatbot

Erwin Boyer

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11 Of The Best Artificial Intelligence Enterprise Chatbots in 2021

Chatbots for businesses help them engage their website visitors and convert them into potential customers. The implementation of chatbots transforms the way businesses interact with their users. They can use a chatbot AI for sales, marketing, customer support, and automate many other business tasks.

The AI chatbots have revolutionized the customer service experience and enabled businesses to serve their customers in a better way. Chatbots, if created and used right, can help you take your business to all-new levels of success.

To make the best AI chatbot for your business, you need an efficient chatbot builder with various advanced features. In this post, we have listed different chatbot builders with their features, pros, and cons. Just go through the post and find the one that best fits your business needs.

chatbot for your business.

#chatbots #chatbot-development #ai-chatbot #customer-support-chatbots #power-of-chatbots #enterprise-chatbots #use-cases-of-chatbots #what-is-a-chatbot

Erwin Boyer

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How To Measure the Success of a Conversational AI Chatbot

We should strive to make data analysis a part of the development process for chatbots to improve features as per the users’ needs, especially in healthcare.

Last year, when one of our healthcare partners (we refer to our clients as partners) were looking to build a conversational AI chatbot, I was apprehensive about guiding them. I had only worked on the level 2 (out of the 5 levels of conversational AI) type of bots. But this time our partner wanted to build a contextual/consultative AI-powered chatbot assistant.

I was concerned about how the bot would understand end-users’ problems. What features can we build to make it more humanistic? Would it be successful in replacing human care and compassion? Would it replicate the same emotions of empathy, compassion, and care?

And even if we managed to do everything, how would we know if the conversational AI chatbot is working the way we designed it? How would we define the ‘success’ of our initiative?

My apprehensions became real when I read a Forbes article about chatbots killing customer service with their clumsy conversations and limited learning capabilities. After reading the below paragraph, I realized the problem—

“The AI didn’t always get it, which was frustrating. Even more irritating—the company using the chatbot seemed to shrug the problem off. I detailed my own experience using Skyscanner’s chatbot, which often misunderstood my requests. Some of the companies I mentioned in the column appeared to shrug off my concerns.”

The problem is with organizations/management who choose to look away and see the importance of data analytics in chatbots for healthcare. They think that understanding the users’ behavior, what disappoints them, what makes them happy, is beyond the scope of their work. Because of this mindset, chatbots are still a lost cause.

Is there a solution in sight?

Yes, indeed there is. We’re at a very interesting place where we hold the future of chatbots in our hands. To make chatbots more welcoming and user-friendly, we not only need to make its software side—engineering, UX design, security—more robust. Rather, we should strive to make data analysis a part of the development process—i.e. we must constantly monitor chatbot’s effectiveness and improve features as per users’ needs.

#chatbots #ai in healthcare #conversational ai chatbot #chatbot analytics #chatbot analysis #how to measure the success of a conversational ai chatbot