Flaq 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.

Kinovi is a web-based AI media generation platform for creators and developers. Its browser-based Studio lets users select from a catalog of video, image, and audio models, submit prompts and supported reference media, and review generated results. The same model routes are available through a REST API, with documentation for authentication, task submission, status checks, uploads, webhooks, model inputs, and usage rates. A shared credit balance covers Studio and API requests; charges vary by model and settings, failed tasks are refunded, and purchased credit packages do not expire. Users can compare models and prices before choosing a workflow, while developers can automate generation and retrieve task results programmatically. Kinovi is suited to creative exploration, media production, and application workflows that need access to multiple AI generation models through one web interface or API.