chatbots Archives - Devtorium

AI Chatbot Development: How Does a Voice Bot Work?

Posted on March 25, 2024March 25, 2024 by mkoftielieva

AI chatbot development is in high demand. Only about 20% of businesses use one, but over 60% think about adopting this technology. At Devtorium, we often work with chatbots because they are of interest to our clients. Today, we’d like to share one of our current cases, where we created an AI chatbot for a client that runs an innovative marketing solution.

The product is a CMS that gathers data through quizzes. The AI chatbot capabilities are required to collect and verify the collected data. In addition, we are expanding the product with an AI-powered voice chatbot that can schedule calls and generally substitute call center services.

Devtorium has a dedicated Research and Development Team that works with different types of AI services. In this case, our developers did all the work, creating the CMS, integrating a messenger chatbot, and developing a voice bot for calls.

How we used AI chatbot development for a case of a marketing CMS.

AI Chatbot Development for a Marketing Solution: Base Product Outline

In this project, the product is a quiz-based CMS that creates a variety of questionnaires based on user-set parameters. The quizzes are flexible so every user can custom-tailor the questionnaire for their business. The CMS makes collecting, processing, and visualizing data easy to help users understand their target audience.

The project aims to create an effective solution that will help businesses generate qualified leads. This product’s text chatbot collects data. The next phase, the voice bot, can schedule calls, initiate APIs, and send messages. Most importantly, the AI can use advanced ML models to understand what the customer says and proceed according to the information received in real-time.

During this project, our software development team used a variety of technologies:

Back-end:

Node.js

Front-end:

React

Databases:

MongoDB
PostgreSQL

DevOps:

AWS
Jenkins
GitHub

AI (phone service):

Vonage

ML models:

OpenAI GPT-3.5(GPT-4)
OpenAI speech-to-text (Whisper)
OpenAI text-to-speech

It’s essential to note that Devtorium always uses a combination of technologies and frameworks to achieve the best results. We discuss the client’s ideas and goals in depth to build a product that can achieve them while staying within budget.

Voice AI chatbot development; step-by-step AI tools involved.

Voice AI Chatbot Development Services Overview

In this article, we wanted to focus specifically on the voice bot designed for this project. Below, we will detail exactly how such a solution works and what it can achieve within the current level of technology. However, we’d also like to remind you that this tech is evolving fast. Almost anyone today can build an AI chatbot using LangChain or similar frameworks. You don’t need a coding degree for that. In fact, some platforms are so user-friendly that they can help you build a basic bot with limited capabilities with no tech knowledge.

However, if your business wants to invest in a solution that will give you a competitive advantage, you’ll need a professional-grade tool. The Devtorium’s lead AI specialist, Oleksii Makarov, outlines how to create an AI chatbot that can talk to your clients.

Voice AI chatbot development starts with VoIP

First of all, when creating a voice bot, we need to use a phone service. VoIP technology is quite advanced today, so this won’t be an issue. We chose to use Vonage because it is currently the best option regarding both quality and service versatility.

Speech-to-text: an essential part of AI chatbot development services

Speech-to-text technology is crucial for building an AI voice bot because it enables the machine to process audible information. We use Assebly.ai in our projects because it currently delivers the highest level of accuracy. Most importantly, it’s able to process information effectively in real-time. Therefore, it helps create an illusion that the user is talking to a person instead of a machine.

While working on this project, we noticed that lag is the biggest issue with these chatbots. Simply put, processing data takes time, so the pauses in their responses are too long. Assembly’s processing capabilities help us reduce this time to manageable levels.

Machine Learning models do the powerlifting in data processing

Devtorium uses the GPT engine versions 3.5 and 4 to build the most efficient chatbots for every application. This technology is the leading AI power behind any voice bot because the solution uses it to process data. Basically, it’s your bot’s ‘thinking power’.

We actively use advanced prompt engineering techniques while designing instructions for the bot’s conversations. The main task is creating instructions that enable the bot to learn and grow. The critical task is to make the conversation sound as natural as possible to a human.

Going back through text-to-speech

Now that the data has been processed and the machine has created the response, we use the GPT-provided text-to-speech tool. It works pretty well for the current technology level. However, we are excited because there are some announcements for more advanced features. In addition, we expect to see more voices and ‘emotions’ options quite soon.

It’s great to see this technology developing and including the emotional aspect of conversations. This truly bridges the gap between machines and people. Most importantly, we are sure this will boost the bot’s ability to deliver higher-quality customer services fast.

Back to the phone service

AI chatbot development is a complex process that includes many steps. However, at the final stage, it returns to where it started. In our case, the Vonage phone service is where the bot talks to the customer.

Voice AI Chatbot Development Benefits

The extraordinary thing about using voice bots is that they do not only cut down the cost of outsourcing call center services. Even with the current technology level, we can create a bot that extracts data from spoken conversations in JSON format. In addition, it’s able to send out a call to third-party APIs.

In simple terms, the bot can trigger an application to run in response to your customer’s query. It will also automatically process all data from the conversation and show it to you in the way you choose. This offers limitless opportunities for studying your customers’ preferences, reactions, and interests. Therefore, a voice bot can become your single most valuable tool for interacting with and researching your target audience. It can also initiate various programs or connect the client to a human operator if the machine cannot process the query.

If you want to see how it could work in practice, set up a free consultation with the Devtorium AI team!

Build an AI Chatbot with OpenAI Assistant API and LangChain

Posted on January 12, 2024January 12, 2024 by mkoftielieva

Technology has progressed so far that you can build an AI chatbot with minimum effort today. The world now really looks like some sci-fi stories come to life. OpenAI is one of the businesses standing at the forefront of this technological revolution.

We talked to Devtorium developers about how OpenAI’s Assistant API is reshaping how we develop digital assistants. Have you ever wondered what the development of chatbots looks like? Devtorium’s developers explore this superb AI-powered tool and share a tutorial on how to build a chatbot with Assistant API and LangChain.

Why Choose Assistant API to Build an AI Chatbot

Developers might have vastly different opinions on whether or not AI code-generation tools are helpful. However, everyone with experience working with OpenAI Assistant API agrees this is a magnificent tool.

Assistants API is an NLP(natural language process) API currently available as a beta version. You can already use Assistants API for question answering, language translation, and code generation. However, its primary function is to assist developers in building chatbots within their apps. To start using Assistants API, you must have an OpenAI API account.

Assistants API uses OpenAI-hosted models, access files, persistent threads, and call tools to respond to user queries. According to Devtorium developers, its most prominent and valuable features are:

Code interpreter and retrieval: Access and execute code from various sources.
Function calling mechanism: Call functions from other APIs.
Knowledge base: Store and access information from a variety of sources.
Easy conversation management with threads: Keep track of the context of a conversation.
Support for different models: Choose the best model for your specific task.
Customizable instructions: Control how your assistants respond to user requests and perform tasks.
Easy deployment: Deploy to a variety of platforms.

How to Build an AI Chatbot with Assistant API and LangChain

The range of AI software development services offered by Devtorium is vast. Therefore, we explored multiple AI solutions and technologies available today. One of our developers’ favorites is LangChain, a framework built around LLMs (large language models) and designed to simplify the creation of complex apps. This tool connects components: prompt templates, LLMs, agents, and memory to create a chain, hence the name LangChain.

In order for LangChain to work correctly with Assistants API, make sure you download version 0.0.331rc2 or higher. The latest RC version of LangChain can support Assistant API using an experimental package. The only class you need is OpenAIAssistantRunnable, which makes code much cleaner.

Now, let’s get on with the guide on how to build an AI chatbot using these tools. Using the tips below, you can make an MnA assistant that will answer queries using a retrieval tool. No Chunking, no embeddings, and no vector database are required.

The steps to build an AI chatbot using this approach include:

Create an Assistant API account and get an API key.
Create an Assistant in the API by defining its custom instructions and picking a model.
Install LangChain and create a LangChain project.
Write a script that uses the Assistant API to send and receive messages from users and access and store information from LangChain.
Deploy your chatbot to a web server, messaging platform, or mobile app.

Technical Instructions on Working with Assistant API and LangChain

1. Set up Assistant API

Sign up for an OpenAI account
Get API key

import openai

     openai.api_key = "YOUR_API_KEY"

2. Create an Assistant

Define instructions for the scope of your chatbot, tools it can access, etc.
Pick a model (code recommendation, text embedding, etc.)

assistant = openai.Assistant("assistant name", model="Davinci")

3. Install LangChain

Install LangChain and LangChain-experimental package
Import OpenAIAssistantRunnable

from langchain.llms import OpenAIAssistantRunnable

4. Handle user input and get assistant response

Take user message as input
Process with OpenAIAssistantRunnable to get assistant response

user_message = input("User: ")

     assistant_response = OpenAIAssistantRunnable(assistant).run(prompt=user_message)["response"]

5. Connect LangChain memory

Store data to use across conversations
Access external APIs through LangChain agents

memory = {"context": {}} 

     agent = ExampleAgent()

     assistant_response = OpenAIAssistantRunnable(assistant, memory=memory, agent=agent).run(prompt=user_message)["response"]

6. Deploy chatbot

Wrap in a web app/API, connect to a messaging platform, etc.

Bottom Line: Who Can Build an AI Chatbot with Assistant API and LangChain

As you can see from the post above, anyone with minimal coding knowledge can build an AI chatbot using tools like LangChain and Assistant API. Of course, an average person with no software development background won’t be able to do this unless they learn extensively.

However, the essential factor is that any small business can now access all the benefits of using a chatbot with minimal investment. All you have to do is contact our team and set up a free consultation. Our experts will discuss your ideas and requirements and come up with a plan that will fit your budget.

No reason for any business to not benefit from a chatbot today exists. So, contact us and take the next step in your tech growth!

If you want to learn more about how Devtorium developers work with AI, check out the following articles:

AI Speaks About How to Use an AI Chatbot for Business

Posted on April 5, 2023August 30, 2023 by mkoftielieva

Devtorim’s AI-powered platform Marquètte is getting better at generating interesting articles you can use for blogs and even for self-education. Today we used one of the new marketing templates to have AI share ideas on using an AI chatbot for business. Check out what it had to say below.

Ideas on How to Use an AI Chatbot for Business in AI’s Own Words

In today’s digital world, businesses increasingly turn to artificial intelligence (AI) chatbots to automate customer service and enhance customer engagement. AI chatbots have the potential to save time and money while providing a more personalized customer experience. In this blog post, we’ll explore how to use an AI chatbot for business, the benefits of using an AI chatbot, examples of successful AI chatbot implementations, challenges of using an AI chatbot, best practices for deploying an AI chatbot, and how to measure the success of an AI chatbot.

How to Use an AI Chatbot to Automate Customer Service

AI chatbots can be used to automate customer service tasks such as:

Answering frequently asked questions
Providing product information
Helping customers with their orders

They can also be used to respond quickly to customer inquiries and provide personalized recommendations based on customer data. By using an AI chatbot, businesses can save time and money while improving customer satisfaction.

Benefits of Using an AI Chatbot for Customer Engagement

AI chatbots can help businesses to provide personalized service. For example, they can answer customer questions 24/7 and provide automated support.

In addition, AI chatbots can collect customer data and improve customer engagement through targeted messages. AI chatbots can save time and money by automating everyday customer service tasks.

Examples of Successful Uses of an AI Chatbot

AI chatbots can be used for a variety of business needs. For instance, the Bank of America uses an AI chatbot to help customers with account inquiries and transactions.

There is also Sephora, a company that leverages AI to power an in-app virtual assistant that helps shoppers find the right products.

Moreover, Domino’s Pizza has created an AI chatbot to take orders and provide personalized recommendations.

Challenges of Using an AI Chatbot for Business

Implementing an AI chatbot for a business can be a challenging process. Designing, developing, and deploying a chatbot requires a lot of time and resources.

Additionally, businesses must consider the cost of hosting and managing the chatbot and other associated expenses. Finally, it may take some time before companies realize their chatbot’s full potential.

Best Practices for Deploying a Chatbot

Deploying an AI chatbot can be a great way to improve customer service. However, it’s important to ensure that the chatbot is designed to meet the customer base’s needs and that it is properly integrated into the existing customer service infrastructure.

Moreover, providing customer service agents with the necessary training to manage conversations with the AI chatbot is crucial. Finally, you also need ways to monitor customer service interactions for quality assurance purposes.

How to Measure the Success of an AI Chatbot

Measuring the success of an AI chatbot depends on the goals you have set. For example, you can measure the number of interactions, user satisfaction and conversion rates, or time on task. Additionally, you can use surveys and feedback forms to gain insights into the user experience.

Final Thoughts: Should You Start Using an AI Chatbot for Business?

AI chatbots can be invaluable for businesses looking to automate customer service and improve customer engagement. While there are potential challenges in implementing an AI chatbot, with the right strategies and best practices in place, businesses can maximize the success of their chatbot. In addition, deploying an AI chatbot is a great way to increase customer satisfaction while reducing customer service costs.

So, those were thoughts directly from AI. What do you say? Do you agree with these opinions and ideas? Will you start using an AI chatbot for your own business?

If you are ready to take this step, set up a free meeting with our development team!

For more thoughts on AI also see:

How Artificial Intelligence Software Development Will Transform in 2023

Using AI for Sustainability: Technology for a Better Future

Using AI for Sustainability: Technology for a Better Future

Posted on March 22, 2023August 30, 2023 by mkoftielieva

Everyone today should understand that our planet isn’t doing too well health-wise. Reports of natural disasters or some other nasty side-effects of environmental changes come almost daily. With the rise of artificial intelligence, we are wondering how using AI for sustainability could help improve this situation. It turns out that AI tech can become a true life-saver for our planet, but only if it’s used wisely.

Artificial intelligence software development technology is developing rapidly. Some of its trends are already focused on using AI for sustainability, but that’s hardly enough. To truly benefit from this tech, people have to invest in the solutions that can make the most difference. However, governments also need to contribute. It’s not only a matter of money but also regulation. It’s because abusing AI tech could lead to tragedies, especially in countries that aren’t liberal democracies.

Keep reading to learn what AI can do to help heal our planet and why we must keep it under control.

Using AI for Sustainability and the UN SDG Program

A giant blob of seaweed moving to the shores of Florida right now is only one of the many natural disasters in action. All of them are red flags waving at the planet’s populace, stating that we need to do something to improve the health of the planet. One of the main initiatives currently working on those objectives is the SDG Program.

SDG stands for Sustainable Development Goals defined by the UN. Those are the goals humanity is working towards to ensure the long-term survival and well-being of our world as a whole. They go far beyond managing climate change, including dramatically important matters like conquering world hunger, inequality, and increasing education quality.

Using AI for sustainability can help achieve over a hundred of those top goals faster and more efficiently. Applying this technology is currently most beneficial in matters concerning climate change and the overall health of our environment.

In turn, this can benefit businesses and economies because we live in a highly interconnected world. For example, according to PwC research commissioned by Microsoft, using AI for various environmental purposes can contribute about $5.2 trillion to the global economy by 2030. That’s not even counting the long-term benefits the entire planet’s population will experience from having a healthier environment.

Using AI for sustainability worldwide could help reduce greenhouse gas emissions by 4% in 2030, which equals the annual emissions of Australia, Japan, and Canada combined!

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Companies Using AI for Sustainability

Many top companies already use AI for energy management and other practices to reduce their carbon footprint. Top examples of this include:

IBM
IBM is applying AI in many of its processes to boost overall business productivity. Regarding increasing sustainability, one of the most valuable contributions comes from using AI for weather forecasting. Artificial intelligence allows for raising the accuracy of predictions by about 30%. As a result, IBM can help renewable energy companies increase their efficiency, especially in resource management and energy production.
Google
It’s no secret that Google takes sustainability projects very seriously. Running power-hungry data centers, the company must do its best to boost energy efficiency. AI helps Google reduce cooling costs by 40%, and that’s only one of its applications.
Carbon Tracker
Carbon Tracker is a think-tank focused on finding ways to improve the climate situation on the planet. One of its projects is using AI for tracking emissions. They can track CO2 based on satellite imagery and use this data to identify coal plants with the lowest footprint. Then, they use the data to help attract investment to these specific plants.
Xcel Energy
It might be surprising to hear that a company that burns coal and has a high emissions level uses AI for sustainability. However, even businesses that are considered non-eco-friendly work on minimizing their impact. Xcel Energy is using AI to increase its efficiency by about 20%.

However, you don’t have to be a huge enterprise that racks up millions in revenue to start using AI for sustainability. You can use this technology to improve your business practices and processes in many ways. Consider the following ways to implement AI:

Precision agriculture
Energy management within office buildings
Analytics for better resource planning
Minimizing energy and water waste
Environmental monitoring
Sustainable supply chains

Why Using AI Might Hamper Sustainability and Cause Global Problems

Using AI for sustainability can help accomplish great things. Some of the most prominent among them are:

Clean power
Sustainable production and consumption
Clean transport
Smart homes and cities
Early warning about possible disasters
Resilient infrastructure
Pollution prevention
Clean oceans
Disease control
Clean water supply
Resource management
Sustainable resource use

These and many other things can be possible if people work together and wisely manage their resources. AI can be a great help by taking out biases and calculating the best strategies for increasing sustainability and equality.

That said, this power can be used for evil as easily as it can be used for good. Therefore, it’s imperative to develop specialized regulatory bodies and strategies to monitor the applications of AI.

One of the most concerning matters is the use of this technology by authoritarian and totalitarian political regimes. Some non-democratic governments are already using AI for tracking purposes. There is a huge risk that they will abuse this technology further in order to maintain power and control of their territories and promote their corruption schemes.

A lack of transparency and competent regulation when it comes to using AI for sustainability or any other purpose can result in tragedies. It will definitely lead to multiple safety risks, including some with possible global consequences. It will also make it impossible to maintain clear ethical standards.

Therefore, any large-scale use of AI should be preceded by the development of proper regulation. Currently, technology is growing and spreading much faster than appropriate political and regulatory protocols. This should be concerning for all of us.

Bottom Line: The Future of AI and Its Impact on the World

Even the most basic AI chatbot can do incredible things today. Therefore, the future of AI technology is certainly bright. It will continue developing and growing fast because it’s the top investment opportunity right now.

However, that growth can lead to unimaginable consequences without proper regulation. So, the question isn’t how we can use AI for sustainability but how to ensure that sustainability is all it’s used for.

Devtorium Software Product Development Company: 2022 Progress Report

Posted on December 29, 2022February 9, 2023 by mkoftielieva

The war in Ukraine, the worldwide COVID-induced supply chain collapse and the global economic crisis are the things that defined the year 2022. Of course, no software product development company remained unaffected by these major factors. As a result, the already competitive industry has become a cutthroat battle for new projects. Devtorium is proud to report that despite all challenges, we are closing the year with new projects, promising negotiations with prospective clients, and mastering innovative technologies.

Devtorium Software Product Development Company: Yearly Report

At Devtorium, we’ve always believed that the true strength of a business is the people. This year provided us with solid proof of that. Our teams turned the trials they faced into opportunities to show their strength of spirit and admirable work ethics. Delivery schedules became the topmost priority for every developer as they refused to get behind on their work regardless of the circumstances.

The results of this dedication and professionalism speak for themselves:

Many of our developers work from Ukraine and struggle with disruptions caused by the war. However, wartime challenges didn’t make us lose a single client. We remain firmly within project deadlines regardless of any power outages and missile strikes.
We’ve started two new projects in 2022. One is a comprehensive insuretech solution that consists of several products. It’s powered by .NET, React, and PostgreSQL technologies and is completely cloud-based (AWS). Another is a React-powered travel app focused on accessibility.
We’ve completed negotiations and will launch two new projects in January 2023. One is a large-scale ad-tech solution powered by .NET and Angular. The other is a verification software product based on Node.js and React.
We’ve launched two proprietary products developed by Devtorium teams. Our AI-powered content generation platform Marquètte is currently receiving a big upgrade with the release of the Templates feature. Now it’s even easier for copywriters to use it for creating top-quality original content. Devtorium also used the Bubble no-code platform to develop our own ERP solution. Our HR and recruiting specialists are currently testing it, and developers are improving the solution based on their feedback.

Devtorium Software Development Plans & Goals for 2023

Devtorium is always looking into the future as a software product development company. We are implementing innovative technologies in our workflows to achieve better results. Our primary focus for 2023 is AI development.

The company already has experience in creating our AI-powered platform, Marquètte. Working on this project has been both challenging and exciting. Most importantly, it gave us the experience of interacting with AI engines and a better understanding of what we can achieve with this tech.

We plan to further this work next year. At the moment, our company is in the process of negotiations for an auspicious AI project. It could result in the development of an AI-powered chatbot for foreign language learning. The team will be creating it from scratch using GODEL by Microsoft.

We are delighted to share that the company is currently negotiating with several prospective clients. Moreover, our potential projects will engage not only our outstanding developers, Business Analysts, and Project Management specialists. In addition, we have plenty of exciting work planned for our Data Science team.

Also, we keep searching for new opportunities constantly. Our sales and marketing teams are always active, looking for clients both online and offline. In January, our American management representatives will present Devtorium at a big conference in Las Vegas. ASW is one of the foremost hubs for IT service networking, so we look forward to this event’s results.

All in all, our work never stops!

Devtorium is proud of what we have accomplished this year, and we are looking at a brighter future with new opportunities.

We’d like to thank our incredible team. None of it would have been possible without you!

What Is Conversational AI? History of Chatbots

Posted on December 14, 2022February 9, 2023 by mkoftielieva

Conversational AI is so much a part of our lives now that we take it for granted. In fact, many people won’t even recognize that they are talking to an AI when interacting with customer support. That’s actually an issue that might cause your sales to drop. We’ll discuss the reasons for it and how to avoid this while getting all chatbot benefits.

It’s vital to remember that technology has undergone a fantastic transformation over the past few decades. Understanding the history of its evolution can help make more accurate predictions about the future of AI. It’s also essential information for those who plan their investments for the upcoming years. So whether you think of it as an investor or as a business owner, putting your money on conversational AI is sure to be a win.

History of Conversational AI: First Chatbot Examples

AI technology became a trend only a few years ago. However, the first chatbot was built in 1966. Named ELIZA, this was a rather primitive program compared to our current solutions. Funnily enough, the idea of ELIZA was to simulate a psychotherapist. Its behavior followed the extremely annoying trend of turning every user’s sentence into a question.

Obviously, ELIZA’s ability to communicate was minimal. We assume that the same goes for its proficiency in therapy. However, it was an important step for chatbot technology development.

The next big chatbot project was PARRY, ‘born’ in 1972. This time, conversational AI was simulating a patient suffering from schizophrenia. It performed admirably well as some psychiatrists couldn’t identify it as a machine while ‘talking’ to it. However, PARRY’s actual ‘talking’ ability was also minimal as well.

We can see a trend here. So, when you use a voice assistant or a chatbot support service today, remember that psychiatrists were the first to work with their creation.

From those first attempts, chatbots kept evolving until the rise of the semantic Web 4.0. This technology gave machines the power to understand context, skyrocketing chatbot evolution.

40% of all user interaction with a support service is purely emotional, so your chatbot must be capable of ’emotion’ as well

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Can Users Tell a Conversational AI from a Human?

Today, conversational AI chatbots are highly advanced and can emulate human interaction well because of sentiment analysis technology. It’s a recent development, and that’s why conversational AI has made several giant leaps in recent years.

To get some idea of how important this is, you should consider that about 40% of all user interaction with a support service is purely emotional. Chatbots based on repetition couldn’t provide valuable interaction in these situations. However, machine learning and NLP changed this. Now, a chatbot in customer service is capable of identifying and processing emotions and sentiments from the user’s request. Moreover, it’s capable of replying with a degree of simulated emotion. That’s what makes conversational AI appear human.

We must mention, however, that our ability to understand whether we communicate with a human or a machine is limited. For example, the PARRY mentioned above, which was a non-advanced system that didn’t even rely on self-studying AI, could fool certified experts. Five psychiatrists interviewed the chatbot in 1979 using teletype to hide the fact that it was a machine. They were supposed to determine whether it was an AI or a real person with a psychiatric disorder. Only one expert could clearly determine the difference between an AI and a real patient.

Imagine how much harder it would be now, when every AI-powered chatbot in customer service learns and improves with every interaction.

Business Impact of Disclosed and Undisclosed Chatbots

The role of conversational AI chatbots has entirely changed with their integration into popular messaging systems. Many brands launched their chatbots to offer services through such platforms. So, today most people interact with some type of AI-powered support through:

Telegram
Viber
Whatsapp
Facebook Messenger

As you know already, conversational AI has been developing to mimic emotional human interaction. Therefore, it’s become hard for people to notice who exactly they are communicating with. Of course, some chatbot services explicitly state they are exactly that. So there is no confusion on the user’s part.

Meanwhile, there are undisclosed conversational AI chatbots. They can achieve fantastic results, especially in sales. Presumably, a chatbot can achieve the level of a specialized shopping assistant. Therefore, it can help retailers increase the number of conversions by providing more personalized top-quality service.

However, should the consumer find out they’ve been interacting with conversational AI during the process, they get upset. As a result, they buy fewer products and might even switch to a different brand.

Apparently, studies indicate that humans consider chatbots to be limited and more ‘primitive’. Therefore, when interacting with disclosed conversational AI chatbots, they use very simple language. Oftentimes, users will bring down the level of their vocabulary when interacting with a program due to their desire ‘to make the machine understand’.

However, humans don’t always do this because they think machines are too primitive to understand human language. The main driving force for this behavior is our understanding that machines are incapable of empathy. At least for the moment, it’s a complete truth. No matter how advanced conversational AI is, it will only mimic human emotion during the conversation.

Is Conversational AI ‘Alive’?

Semantic Web 4.0-level technology can identify and interpret human emotion (to some degree) when processing data. Therefore, conversational AI chatbots are capable of interacting with humans more efficiently and appear more alive. So, it’s harder for users to understand if they are dealing with a human or chatbot in customer service. In fact, chatbot help turns out to be about four times more efficient.

However, humans are creatures prone to bias. Thus, as long as we are stuck believing that machines are incapable of understanding and projecting emotion, we will be uncomfortable with them doing it.

As you can see, issues discussed in science fiction novels decades ago have become our reality today. AI chatbots aren’t ‘alive’, but they learned how to mimic humans better. Combined with the outstanding processing power of artificial intelligence, we can expect this technology to become even more helpful and ‘human-like’ soon.

A chatbot is FOUR times more efficient in customer support.

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Conversational AI Chatbots Vs. Assistants

Advancements in conversational AI technology mean that its applications are growing. Similar to how computer vision tech goes into everything from self-driving car navigation to facial recognition software, conversational AI helps create different programs.

Of course, the most numerous are AI chatbots, which provide various support and educational services. However, today this technology has become a big part of the rapidly-developing AI-powered virtual assistants industry. Leaders among them are:

Siri (Apple)
Cortana (Microsoft)
Google Assistant
Alexa (Amazon)
Watson (IBM Cloud)

The difference between conversational AI chatbots and assistants is that while both are conversational interfaces, they fulfill different roles. A chatbot in customer service will answer questions and offer suggestions based on preset parameters. This type of software follows the same pattern when used in education as well. Basically, it’s a machine that provides information based on a prompt from the user.

Meanwhile, virtual AI-powered assistants help you with everyday tasks. Their features are versatile, for example, reminders, to-do list management, search assistance, note-taking, etc. In essence, this solution is your personal secretary. In addition, these assistants can be connected to smart devices and integrated into your IoT network. So, you might be able to manage most of your house through voice commands and your smartphone. That voice command feature is powered by a version of conversational AI.

Although they apply this technology differently, chatbots and virtual assistants run on the same principles of AI tech. Moreover, we can expect both these branches of conversational AI to keep growing at an astounding pace.

Bottom Line: Who Needs Conversational AI Products Today?

To put it simply, every business, both big and small, can benefit from implementing AI chatbots in some processes. They are good for automating routine tasks, like basic consultations and surveys. You can also use them to provide higher-quality customer support. It can be a huge advantage for small businesses, in particular.

Moreover, you can use bots powered by conversational AI for education and onboarding. Therefore, big companies can implement them to increase the productivity and efficiency of their overall operations.

There is no shortage of conversational AI chatbots applications, so you should definitely consider adding them to your business arsenal. Contact the Devtorium AI team to learn how this technology can benefit your business. We can build chatbots from scratch to ensure that the solution is custom-tailored to your needs and can grow and scale up alongside your company.