What Is Qlik Answers?

Perhaps the biggest announcement of Qlik Connect 2024 was that of a new product: Qlik Answers. At the time, it was promised that Qlik Answers would launch in July of that year. And that's exactly what happened: as of July 31, Qlik Answers has been available to the general public. In this blog, we explain what Qlik Answers is, what you can do with it, and what you (still) can't.

Retrieval Augmented Generation

Qlik Answers is an application of the technique known as Retrieval Augmented Generation (RAG). You might immediately wonder: what is Retrieval Augmented Generation? To explain this better, we need to start with generative AI techniques such as ChatGPT:

By now, you've probably used ChatGPT at some point. It works like this: you ask a question in plain language and get an answer back in plain language. However, there are two important caveats to the answers you get from ChatGPT:

• Hallucinations: First, there's the chance of so-called "hallucinations". The answer you get sounds convincing, but is partly or entirely
  made up.
• Not up to date: The other major limitation of ChatGPT is that it's limited to a certain point in time. To train the model, OpenAI's developers feed it with all publicly available information on the internet. The problem with the internet, though, is that millions of new pages and articles are added every day. To keep the training of the model from going on forever, the developers set a cutoff. The current most recent model, GPT-4, for example, was trained on data up to April 2023. If you ask ChatGPT about Apple's stock price this month, for instance, it will tell you it has no answer to that.

With Retrieval Augmented Generation, the language model is extended with search capabilities. When you ask a question, the language model won't make up an answer itself; instead, a function is called that searches for the right answer in a predefined source. Once the answer is found, the language model is used to present that answer back to the user in plain language. This approach solves the problems above: the function being called is able to look at new information that may not even have existed when the language model was trained. In addition, RAG can include a reference in the answer to the sources consulted by the called function, so you can always verify the accuracy of the answer yourself.

How does it work?

To get started with Qlik Answers, you'll first need to define which sources can be used to answer users' questions. This is made very easy in Qlik Answers: you can upload documents by hand, or connect to a storage location such as OneDrive, Amazon S3, or Google Drive where these documents live.

In the knowledge base, you upload the files your assistant bases its answers on

The set of documents you upload become part of a so-called "knowledge base". Once the documents are uploaded, you click the "index all sources" button. This button essentially causes Qlik Answers to read through the documents and try to understand them as well as possible, so it can later use the content to answer questions.

Once you've created one or more knowledge bases, you can create what's called an assistant. This assistant is essentially the chatbot you can talk to. You then link one or more knowledge bases to an assistant. The big advantage of this approach is that you have great control over which information may or may not be used to generate answers for different user groups.

You link an assistant to 1 or more knowledge bases, after which you can start asking questions

Once you've created the assistant, you're done, and your users can get started asking questions. Once an answer has been generated, you'll see four buttons in the answer's speech bubble. First, there are the thumbs-up and thumbs-down buttons. Your users can press these when they're happy with the answer, or when they didn't get the answer they were looking for. As a developer, you can find this feedback later, so you can see where the gaps in your knowledge base are. There's also a button that lets you easily copy the text of the answer. The last button is labeled "View x sources". When this button is pressed, a second panel opens, showing the pieces of text the answer is based on. This window also includes a download button right away, letting the user download the original document.

Applications and limitations

With Qlik Answers, Qlik now also has a product in its portfolio for extracting value from unstructured data. For many Qlik users, this is naturally still a relatively unfamiliar area. A logical question, then, is: how can I apply this in my organization? The possibilities seem endless, but to help get you started, we've listed a few ideas here.

• Make onboarding colleagues a lot easier by deploying Qlik Answers as an assistant. You can add all the manuals and work instructions for a department as sources here.
• Bundle all product specifications, frequently asked questions and answers, and past support requests to let your support staff find an answer even faster
• Combine applicable laws and regulations with internal policy documents and procedures so your employees can easily answer legal questions

Surely many more applications are conceivable. The longer an organization has existed, the more documents it has on hand. So with this first release of Qlik Answers, a whole lot of new possibilities open up right away. There are, however, a number of limitations you need to keep in mind:

• Qlik Answers can't yet read images and can only work with text files. A scan of a handwritten document, for example, can't yet be processed properly.
• It's also important to realize that tables can be read in, but can't yet be used to answer questions. So if, for example, your document contains a table with revenue per department for the past quarter, you unfortunately can't yet query that based on the document.
• It's currently not yet possible to combine unstructured data with structured data, such as that in Qlik dashboards. It's reasonable to expect that Qlik is working hard behind the scenes to make this possible, especially since Qlik Talend Cloud already offers the ability to generate so-called "AI-ready" data products.
• Finally, it's good to realize that you're now tapping into a new type of data source with Qlik Answers. Where we've often already put measures in place around data quality and data governance for structured data, that's often not yet the case for unstructured data. To really make a success of Qlik Answers, you'll need to start thinking about measures in this area too.

In short, with Qlik Answers you make valuable information in those documents a lot more accessible for all your employees. This can be enormously valuable in your journey toward data-driven working. Do you have a great use case for Qlik Answers, or want to explore Qlik Answers further? Let us know, we're happy to think along with you!

Written by Lennaert van den Brink
Senior Consultant