Legacy background checks require manually pulling disorganized data from disparate sources, sorting through inconsistent language, and juggling ever-evolving regional compliance laws. We've rebuilt the background check with technology at its core. Our platform uses artificial intelligence to help you hire quickly without sacrificing accuracy or compliance.
Our Charge Classifier uses machine learning to quickly categorize criminal charges from jurisdictions across the U.S., making charge language clearer and drastically reducing the amount of time spent on manual review.
Background check compliance violations and litigation can cost companies millions. Checkr’s compliance engine helps you keep up with evolving regional compliance laws, so you stay ahead of the curve.
AI can identify, classify, and filter data in a fraction of the time required by manual, legacy processes. You can screen candidates faster, with fewer resources.
While other consumer reporting agencies are forced to process every record manually, our machine learning tools categorize data clearly and consistently. Processing over 1.5 million background checks per month, Checkr's platform is constantly learning, giving our customers greater clarity and control.
In addition to helping you hire faster, our technology can help you comply with complex regional regulations. Our Compliance Engine filters out any information that is not legally reportable, and we continuously update our products based on new legal developments.
Background checks are critical to gaining an understanding of your risk before hiring a candidate, but once a background check is complete, the results remain static and soon fall out of date.
Our proprietary data network leverages multiple criminal data sources and the millions of background checks we process each month to help you stay on top of new, reportable charges connected to your workforce. Our proprietary data network is a key part of Checkr’s continuous monitoring services, which help alert your team to safety incidents faster.