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How You Can Use Your Custom Data for AI

1. Introduction

Artificial intelligence (AI) is rapidly changing, especially with tools like ChatGPT. These AI tools are great at understanding and analyzing lots of written documents. This skill is opening up new use cases for companies. In this article, we will focus on how these AI models work best with text data. For example, imagine an AI model sorting through thousands of customer service emails to find specific information, something that would take a human hours or days to do.

2. Types of Custom Data

When it comes to custom data that can be utilized in AI applications, we generally categorize it into two types: internal and external data. 

Internal data

Internal data primarily consists of text documents, knowledge bases, and documentation unique to your organization. This can include reports, internal communications, technical manuals, or any other type of written material that’s used within your company.

External Data

External data encompasses publicly available information like websites or APIs, as well as customer data. This could range from publicly posted articles and news feeds to data collected from customer interactions and feedback.

A company can use both types of data when using AI but it should be aware of the different requirements that a respective data type inhibits (i.e. data security, compliance).

3. How to Use Custom Data with AI

There are several ways to work with custom data, which is why he will present the most prominent ones in the following paragraph.

Chatbots

Chatbots are currently a well-functioning user interface for working with AI and for integrating customer data into these conversations. The most well-known example of an AI chatbot is ppt, which you have most likely already experimented with.

Chatbots offer the simplest and most generic interface, making it well suited for generic interaction with AI models. While this type of interaction works well for some tasks, other interfaces might be better suited for other, more complex tasks.

Workflow Software

Workflow software generally allows users to create customized workflows that automate or augment their very specific tasks. Such workflow software has also existed independently of AI, and has been able to automate previously manual tasks quite well.

The combination of AI models and workflow software can be very powerful. For tasks where a chatbot interface does not provide the best user experience, using workflow software to map a custom process could work much better.

Custom Software Development

A third type of interface for working with custom data and AI could be the development of custom software. Even though many use cases can already be solved via the generic chatbot interface or the very flexible workflow interface, there may still be some use cases where custom software development is the best solution (e.g. edge solutions). 

As we at ValueFlow concentrate on non-technical users, this third and rather rare option for individual software development will not be described in detail in this article.

4. Conclusion

With the current advances in AI, the technical possibilities of analyzing and working with your user-defined (text) data are possible and bring great benefits.

As a business user, you should always consider whether you are working with internal or external data and whether the data in question is sensitive (e.g. customer data or internally sensitive data) or non-sensitive.

Depending on the use case, different user interfaces or tools will work best for you. Chatbot interfaces are great because they are very flexible and easy to use. Workflow software offers you potentially the most powerful use of AI technology in a non-technical way.

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