Hume AI

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.

EchoDepth is an Emotional Risk Intelligence platform from Cavefish. It measures how communication will land before it is delivered, scoring delivery risk across video, voice and text. Unlike sentiment analysis, which classifies language as positive or negative after the fact, EchoDepth analyses observable delivery signals and returns scored, timestamped reports showing where audiences disengage and what to change. Measurement is built on the Facial Action Coding System standard: 44 Action Units calibrated across 14 cultural cohorts in 6 countries, rather than generic image classification. EchoDepth reports what the facial muscles did, not what emotion that represents, leaving interpretation to context-aware human review. For regulated deployment this is the defensible architecture. Typical applications include earnings call and investor communication review, FCA Consumer Duty vulnerability detection, contact centre escalation prevention, interview consistency scoring, and defence