What is Training Data and Why is it Important?

Training data is labeled data used to teach AI models or machine learning algorithms to make proper decisions.. For example, if you are trying to build a model for a self-driving car, the training data will include images and videos labeled to identify cars vs street signs vs people. If you are creating a customer service chatbot, the data may be all the different ways to ask "what is my account balance?" both in text and audio, which is then translated to different languages.

Training data is paramount to the success of any AI model or project. Think of it as garbage in, garbage out. If you train a model with poor-quality data, then how can you expect it to perform? You can’t and it won’t. You may have the most appropriate algorithm, but if you train your machine on bad data, then it will learn the wrong lessons, fail expectations, and not work as you (or your customers) expect. Your success is almost entirely reliant on your data.


Training data isn’t labeled or collected on its own. Human intelligence is required to create and annotate reliable training data. Our high-quality training data is possible thanks to our:


Our platform collects and labels images, text, speech, audio, video, and sensor data to help you build, train, and continuously improve the most innovative artificial intelligence systems. In addition to specialized and precise tooling, we offer several machine learning assisted tools to enhance quality, accuracy, and annotation speed.


To produce the volume of training data required to confidently deploy world-class models, you’ll need an army of contributors and an experienced crowd management service to ensure annotators are identified and certified to your specifications. We are proud to offer a crowd of over one million contributors, in over 130 countries, and supporting over 180 different languages.


With over 20 years of experience scoping and delivering more than 6,000 ML projects, we understand the complex needs of today's AI projects. Our solutions provide the quality, security, and speed used by leaders in technology, automotive, financial services, retail, manufacturing, and governments worldwide.

Types of Training Data


Deploy text-based natural language processing with data that’s collected, labeled, and validated in a wide array of languagesd.


Add computer vision to your machine learning capabilities by collecting and understanding image classification, or leveraging pixel labeling semantic segmentation..


Build interfaces that process audio with data that is collected as utterances, time stamped, and categorized across more than 180 languages and dialects..


Combine the best of audio and image annotation to process video and turn it into actionable training data for machine learning. Teach your model to understand video inputs, detect objects, and make decisions..


Leverage even more data points by annotating data coming directly from sensors and enable machine learning models to make decisions on a variety of data sources including LiDAR and Point Cloud Annotation...