A 2019 survey by McKinsey says that the majority of executives who have adopted AI solutions for their businesses report an increase in revenue, with 44% also reporting a reduction in operating costs.

Indeed, artificial intelligence (AI) and machine learning (ML) models have shown that, when robustly trained and properly deployed, they can deliver significant benefits to businesses and help them to grow their bottom lines.

That said, developing fully bespoke AI models from the ground up can be a challenge; it’s a costly and time-consuming process that’s easy to get wrong. Not only is there the risk that a model that has been improperly developed and trained could do more harm than good for a business (e.g., by being fed the wrong data), but an AI model might fail to even have a meaningful impact on the business, even if it’s well made.

Creating your own AI models doesn’t need to be difficult

This challenge has led to a surge in tools and platforms that enable businesses to build useful, powerful, and cost-effective AI and ML models quickly and easily. There are hundreds of different platforms each with their own use cases and varying scopes of complexity.

For example, some platforms will require you to have one or two software engineers onboard (low-code AI platforms) whereas, with others, no engineers are needed, all you need is an idea (no-code AI platforms) and some good quality data that has been processed and labeled already.

This is important: Your datasets need to have been processed, tidied up, and labeled before you use an AI model builder. This ensures that to get the best possible output from it.

If you already have your datasets but don’t have the labeling part completed, you can use our data labeling tool – Tasq – to do it for you.

Our platform is highly optimized and intuitive, capable of being used to complete the most complex data labeling tasks at a fraction of the cost and time of an old-school data labeling project.

Learn more about how Tasq can unleash the full power of your datasets:

How to build your own AI

Once you’ve got your data processed and labeled, it’s easy to get yourself a working AI model by using a dedicated AI model builder or other platform-style solution. Let’s take a quick look at some of the no-code and low-code solutions that are currently available.

No-code solutions

No-code solutions are exactly what they sound like: They’re designed for people who have some or even no programming experience outside of machine learning who want to build an AI model without having to code it.

Google AutoML

AutoML enables developers with limited machine learning expertise to train high-quality models that meet specific business needs. AutoML includes a suite of products that cover sight and language. It also includes a product that enables users to automatically build and deploy models based on structured data.


Levity is a productivity tool that enables teams to create their own AI for documents, images, and text that eliminate repetitive tasks. This is achieved through full-scale workflow automation that can be achieved without having to write a single line of code.

Teachable Machine

Teachable Machine is a web-based tool that makes creating machine learning models fast, easy, and accessible to everyone. It can be used to train models and build machine learning models for websites, apps, and more.

Low-code solutions

Low-code solutions are a little more advanced than no-code solutions and assume that users will have some formal machine learning experience but are still below the level of an expert. Low-code solutions require some development input from engineers.


H2O.ai is a full-scale platform that enables developers to build their models with accuracy, speed, and transparency. Developers can use the platform to streamline the performance of these models and deliver solutions to end-users from within.


PyCaret is an open-source, low-code machine learning library in Python. It enables developers to go from preparing their data to deploying their ML models in just a few minutes.

Amazon SageMaker

Amazon SageMaker is a cloud machine-learning platform that enables developers to create, train, and deploy machine-learning models in the cloud. It also enables developers to deploy ML models on embedded systems and on the edge.

Get your free demo of the Tasq platform

If you would like to find out more about how the Tasq platform can help you get the most value out of your datasets, contact us or request your free 30-minute demo today!