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1-click AI: The perfect blend between conversational AI agents and ChatGPT

Chief of AI

As Conversational Artificial Intelligence continues to revolutionize business operations, ChatGPT has emerged as Deus ex machina with a wealth of opportunities in improving customer experiences. From small businesses to large corporations, ChatGPT has generated a great deal of excitement, as it offers an innovative solution for improving customer service and streamlining operations.

Although ChatGPT is very easy to use, it is not immediately clear how businesses can fully leverage this innovative technology. Businesses that wish to integrate Conversational AI Agents use a Conversational AI Platform (CAIP), which allows them to design, deploy and manage virtual agents (chatbots) that are tailored to business-specific use cases.

When it comes to AI-powered customer service, not all CAIPs are created equal! The Return of Investment (ROI) for businesses varies significantly depending on which CAIP they use. The ROI depends on two main variables:

1.The amount of time and effort it takes for businesses to create, maintain and improve an AI virtual agent.
2.The percentage of total conversations with end customers that the virtual agent can automate.

At Moveo AI we collaborate with businesses trying to adopt conversational AI every day. Most of them hesitate to adopt this technology, because of four main reasons:

  • Lack of resources to invest into incorporating a new technology
  • Complexity of implementing an AI virtual agent
  • Limited amount of data accessed by the AI virtual agent
  • Uncertainty about the ROI of integrating conversational AI

That’s where Moveo AI comes in with a powerful platform, coined as 1-click AI. 1-click AI makes complex AI technology accessible and simple to use, empowering businesses to make the most of their data, scale their operations with ease and offer the best customer experience.

Lack of resources to get started

Automating business processes can provide significant benefits, but many companies are hesitant due to its demand for substantial upfront investment. In the current conversational AI landscape, businesses often realize that creating AI virtual agents requires many full time employees for a long period of time. Here is why the initial investment for businesses is very costly:

1.Manually collect and curate all conversation flows that the AI virtual agent should cover. For example, a conversation flow could describe how the AI virtual agent responds to the question, “What is the ATM deposit limit”. Depending on the needs of the business, the number of conversation flows ranges between 20 to 500. As you can imagine, collecting and mapping out all conversation flows can be a time-consuming task.

2.Get acquainted with the CAIP specific concepts such that the conversational flows can be converted into data that the AI virtual agent can be trained on and later execute. Current CAIPs require the conversation flows to be in a specific format. Hence the business needs to spend time to first learn this new tool and its abstractions like Intents, Entities and Dialog flows. This is a non-trivial task!

The learning curve associated with adopting a CAIP is a significant factor that discourages businesses from creating an enterprise AI virtual agent. Even for CAIPs that employ a no-code platform, the manual work that needs to be done along with the obscure platform-specific concepts negatively impact the ROI.

Implementation Complexity

Even if a business is willing to commit the upfront investment to create an AI virtual agent, manually creating the conversation flows in the CAIP is quite complex. Even for no-code platforms, a significant amount of technical know-how is required. Without a technical background, trained employees will likely struggle to meet the challenge and will not be able to create an AI virtual agent that meets the company’s demands. You might think that this applies to any B2B software, but in this case, company employees need to become familiar with AI concepts, which can be overwhelming, especially for those who are not tech-savvy.

Creating an AI virtual agent is complex. but businesses must also learn how to maintain them to meet ever-changing customer demands and keep them up to date. Businesses that do not update their AI virtual agents end up with an outdated and mediocre end result. Such an agent fails to consider the actual questions of the end customers and therefore does not fulfill its initial promise of improving the customer experience. Manually maintaining the AI virtual agent is both time-consuming and expensive for businesses. Significant resources must be allocated to constantly evaluate analytics and historical chat logs, gather the negative ones, and implement fixes without breaking any existing flows. Due to the complexity of implementation and high maintenance costs, most CAIPs charge additional fees for both. As a result, the ROI gets negatively impacted.

Limited Amount of Accessible Data

As described above, the AI virtual agent created through a CAIP requires training data in a specific format that is time-consuming and challenging to create. The manual and complex process of collecting and creating conversation flows often leads businesses to only implement a specified amount.

As a general rule, businesses using a CAIP follow the 80/20 rule, which assumes that 80% of the customer questions have to do with 20% of the overall questions that a company should have. For example, if a company could automate 20% of the most asked questions, then 80% of the total conversations would be resolved by the AI virtual agent.

Therefore, businesses only implement flows for the questions they expect most customers to ask. Consequently, less frequently asked questions are excluded from the AI virtual agent and cannot be answered when the need arises. Following the 80/20 rule, even the best AI virtual agent in the world can only achieve a 80% conversation containment rate. Current state-of-the-art algorithms can achieve 80-90% containment, and hence, the final containment rate for an AI virtual agent is at best around 60-72%.

Return of Investment

At the end of the day, businesses care about two things:
1.Improving Customer Experiences
2.Increasing their ROI

These two goals are related.
In the context of customer service, improving the customer experience involves providing quick response times, personalized and accurate responses, 24/7 availability, and offering omni-channel access. It is clear that an ideal AI virtual agent that accomplishes all of these tasks would improve customer experience.

Thus, the decision to deploy an AI virtual agent comes down to the ROI, which depends on the CAIP used. The larger the ROI, the greater the incentive for a business to use a CAIP.

In the context of conversational AI, the ROI is maximized when the CAIP used requires a small initial investment and ongoing maintenance costs while also enabling a high percentage of customer conversations to be handled by the AI virtual agent.

As analyzed above, most CAIPs require a significant upfront investment and maintenance cost. At the same time, the AI virtual agents do not reach their full potential due to the limited amount of data they have access to. This results in an unfavorable ROI for most CAIPs, leading many businesses to decide against implementing an AI virtual agent,

Enter 1-click AI

Our “eye on the customer” mentality has allowed us to identify all the concerns that businesses have when implementing an enterprise AI virtual agent. This puts us in a unique position to address all of those concerns and provide a platform that is easy to use, cost-effective, and empowers businesses to offer the best customer experience. How?

Our 1-click AI painlessly ingests unstructured data sources, allowing enterprises to easily automate any business process.

How it works

1-click AI is as simple as it sounds:

1.A business uploads their knowledge base, website, PDF documents or any relevant data course to the Moveo AI platform

2.Optionally, a business can use Auto Builder to automate their business processes end-to-end such that the virtual agent can also perform tasks, such as rescheduling a package or creating a HubSpot lead

3.Connect the desired communication channels such as WhatsApp, Instagram, or Webchat

4.Monitor Analytics and gain insights by analyzing first-party data

With limited effort, businesses can deploy conversational AI agents that can answer the majority of users’ questions in a matter of hours. Not only does 1-click AI makes it extremely easy for enterprises to create AI virtual agents, but also employs state-of-the-art NLP models to ensure that the agent provides an immersive customer experience. AI Virtual agents by Moveo AI are able to resolve customer issues end-to-end, while also providing humanlike responses resulting in a more natural and engaging experience for customers.


The need for businesses to automate customer service needs is apparent and more urgent than ever before. While most current conversational AI platforms can provide significant assistance, the ROI for business is questionable because of the significant implementation effort and ongoing maintenance costs required. Moveo AI addresses those problems with a powerful platform coined as 1-click AI. With its ability to eliminate the learning curve, minimize upfront investment, and self-improving capabilities, 1-click AI empowers businesses to scale their operations and offer the best customer experience.

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1-click AI

Utilize your data and automate your operations with Generative AI

Auto Builder

Utilize your data and automate your operations with Generative AI

1-click AI

Utilize your data and automate your operations with Generative AI

1-click AI

Utilize your data and automate your operations with Generative AI


1-click AI

Utilize your data and automate your operations with Generative AI

Auto Builder

Utilize your data and automate your operations with Generative AI

1-click AI

Utilize your data and automate your operations with Generative AI

1-click AI

Utilize your data and automate your operations with Generative AI