Artificial Intelligence & Machine Learning

Leverage AI/ML to create intelligent systems that can learn from data.

The Rocketmakers AI Guidebook contains everything you need to get started on your AI journey.

Download the AI Guidebook below!

You'll learn: 

  • How to leverage AI in your business
  • 12 ways to use AI in a Digital Product
  • What are the pitfalls and how to avoid them!
  • Plus much, much, more!

The Rocketmakers AI Guidebook contains everything you need to get started on your AI journey.

You'll learn: 

  • How to leverage AI in your business
  • 12 ways to use AI in a Digital Product
  • What are the pitfalls and how to avoid them!
  • Plus much, much more!

What is Artificial Intelligence (AI) and Machine Learning (ML)?

AI (Artificial Intelligence) and ML (Machine Learning) are technologies that enable computers to learn and perform tasks without being explicitly programmed - taking training data to create rules or networks and applying inferences to then make predictions on other data.

Why is Artificial Intelligence & Machine Learning important?

Benefits can include faster and improved decision-making, automation of routine tasks, enhanced customer experience, improved productivity, reduced errors and biases, and identification of new business opportunities through data analysis and prediction.

The Rocketmakers Approach

Our team includes practitioners who have been working with core ML and AI technologies for many years

Typically in the design and implementation of predictive engines which will present selected content based on previous profile or behavioural data.

In order to get effective AI / ML outputs we focus intently on both the quality and quantity of data available. Often the data quality used as an input to the ML models is a direct result of the user experience we have designed and therefore the various ML algorithms being used need to be selected fairly early in a project in order to help inform that design process.

Illustration of people working over stacks of paper

Our Machine Learning and Artificial Intelligence specialists typically start by building systems using a prototyping approach to help inform the specific input data and the types of output and levels of certainty needed.

This lends itself to specific models being adopted and tested and the supporting application architecture being designed and then built.