Do you do AI at DabApps?

This is a question we get asked a lot, and the short answer is - yes!

AI has been in development for decades, but with the recent increase in visibility and application to everyday objects and lifestyles, it’s now on everyone’s radar. Both existing and new clients have been asking whether there is opportunity to bring AI into their applications.

AI is vast, with multiple strands, and the possibilities are endless. We’re going to talk about a few ways AI could be applied to the type of applications we design and build here at DabApps.

The first thing to note is that we encourage the use of AI to add to the user experience and to save the user time. We strongly believe that the focus should always be on the user and the service your users receive. Used correctly, AI can bring value and growth to a product, and we’re extremely excited to be working in this rapidly evolving area.

Here are some of the ways our clients could use AI in their applications to improve the user experience, and offer a service which users would find useful:

1. Data and Data Analysis

Some of our clients have large databases which can be used for analysis. By integrating AI, the platform could throw up statistics and conclusions which might be interesting to users. For example, it could voluntarily throw up the highest performing employee in your organisation (according to the parameters you have first defined).

2. Predictive data

If clients have a series of data over time, then AI can be used to predict future data points. This can be used to suggest trends, and be used for both positive and negative predictors. For example, if the trajectory is positive, you could use it to predict the point at which a user will hit a certain goal. If the trajectory is negative, you could use it to predict where things would end up, without intervention.

3. LLMs.

We’re all familiar with chat GTP, and let’s be honest, it’s helped us all out in a fix! LLMs can be used within applications to allow users to query more than just the data set. It can be used to provide insight on further actions. So for example, if I have looked at my dataset and seen that Emma is consistently the top performing employee, I might then go on to use an LLM to generate ideas of ways that I can keep Emma motivated and engaged in their work.

But, AI sometimes isn’t the best solution, and/or it can come with complications.

In example 3 here, LLMS, there are a few factors to consider. If you use your own custom built LLM, you have much more control over the content it draws on for its answers. This means you can keep it relevant and focused, and stop users going off on an unrelated tangent within your application.

On the other hand, a custom built LLM is much more expensive, and whilst not prone to the bias that something like chat GPT is (it draws on content from sites like Quora and Reddit), it is of course, then prone to other bias.

There are also ways you can build a similar functionality without needing to integrate an LLM at all:

By using a search tool with your dataset and setting some predefined queries, as well as the parameters which pull up results from these queries, users can feel like they’re using an intuitive service which is saving them time and brain power. You could even have your application randomly choose one of these queries to throw up the answer to, upon landing on a particular page of your app. Again, intuitive and interesting, but not necessarily AI…

So there are many ways that AI can be used in the web and mobile applications that we build. Done right it can add huge value to your product. But done wrong, or for the sake of it, it may just be budget better spent improving the overall user experience – as always, we’d recommend user feedback and making data driven decisions

Our team has a huge range of skills, many of which are applicable to AI engineering – from programming to data science, NLP, problem solving, mathematics and statistics. We’re looking at how we can enhance user experiences for our clients, and for ourselves in our working lives. We’ve also been attending the brilliant Brighton AI meetup, run by volunteers, bringing together experts and learners to discuss AI and its application across a range of sectors. Our MD Catrina is hoping to be part of the committee, working with others in Brighton to establish how AI will impact the local economy, and how we can collectively use it as a force for good in our home city.

So, if you want to build AI into your product, let’s have a conversation about it – we’d love to help you figure out the best direction to go, and how it can most benefit your users.

It’s exciting times in terms of AI, who knows where we’ll be, and what we’ll be able to offer a year from now.