SafetyKit

Amazon Rekognition makes it easy to add image and video analysis to your applications using proven, highly scalable, deep learning technology that requires no machine learning expertise to use. With Amazon Rekognition, you can identify objects, people, text, scenes, and activities in images and videos, as well as detect any inappropriate content. Amazon Rekognition also provides highly accurate facial analysis and facial search capabilities that you can use to detect, analyze, and compare faces for a wide variety of user verification, people counting, and public safety use cases. With Amazon Rekognition Custom Labels, you can identify the objects and scenes in images that are specific to your business needs. For example, you can build a model to classify specific machine parts on your assembly line or to detect unhealthy plants. Amazon Rekognition Custom Labels takes care of the heavy lifting of model development for you, so no machine learning experience is required.

We empower cutting-edge trust and safety teams to better understand their data, streamline decision-making, and measure effectiveness. All from a single place. Protect your users more efficiently and with greater precision. Cinder integrates your critical trust and safety data, freeing your team from spreadsheets, CRMs, and complex SQL queries. By centralizing decision making around your policies, you can finally provide your team with the right data needed to make a decision, fast. Cinder unifies the data and context needed to help your team make faster and more accurate decisions. From individual content review to advanced investigations and case management, Cinder provides a strategic vantage point allowing your team to operate efficiently from a single place. Through customizable metrics and dashboarding, Cinder provides the clarity of vision required to make more confident decisions. Top teams rely on Cinder to help manage complex integrity operations.