In the age of computing 2.0, labeled data is the new code. Learn how and why data annotation is used in your industry.
“We found working with Ango team professional, progressive, and scalable. We appreciate how the Ango team proactively seeks feedback and holds themselves accountable. Their QA team is careful, quick, and responsive, and their high-quality work has led to impactful and timely results.”
Aerial imaging is quickly becoming a key element in agriculture. Without the need for surveys on land, an AI trained on annotated data can have a look at a satellite image and tell you with confidence what the status of your crops is like, what the weather is like, and more.
AI can give your cameras superpowers. Detect which product is which from just a single image. Take a quick video of your store shelves and get a percentage of how full they are. Automatically download pictures from social media and detect what’s fashionable.
And much more.
Manually checking documents takes an inordinate amount of time, effort, and resources. Banks and government agencies using AI to do so can lead to a thousandfold increase in productivity.
And manual checking can still be employed when the AI isn’t sure about a specific document.
Future-facing insurance companies are using AI to automate how they assess and appraise damage.
In the old days, someone had to manually check each picture. With annotated data, you can train an AI to automatically appraise the damage for you.
One of our insurance customers adopted Ango On-Prem for their appraisal process, and does not look back.
Automatically detect and measure traffic on a road, or superpower your car with semi- or fully-automated driving experiences. Detect pedestrians, traffic lights, road signals, construction, curbs, and anything else to make your vehicle more autonomous.
Manufacturing companies are introducing AI into their workflows to automatically detect manufacturing defects, measure production time, increase worker safety, among others.
With annotated data from a CCTV, you can create an AI model to automatically measure production quality, detect whether safety measures are being followed, and a lot more.
Forward-looking health institutions all around the world are looking to semi-automate the process of assessing medical imaging.
This way, the AI can make an educated guess, and the radiologist can spend less time on more obvious cases and focus their attention where a human is most needed.