Photobucket developer Mike Knowles was looking for a quick and easy way to implement machine learning-based image recognition technology in his tech stack. After ruling out building machine learning in-house as too costly and inefficient in the long-run, Mike decided using a computer vision API would be the best way to validate his idea and go to market quickly. He tested half a dozen computer vision APIs including Google Cloud Vision and Amazon Rekognition before deciding that Clarifai offered the best possible solution for his business.
Mike selected Clarifai based on the superior accuracy and ease of use of the technology, the transparency of the online demo, the completeness of the documentation, and the enthusiasm and professionalism of Clarifai’s team. He was also excited about the wide range of computer vision models Clarifai has to offer, including the General model that recognizes over 11,000 concepts and the Moderation model that currently recognizes different levels of nudity (e.g. explicit and suggestive) along with gore and drugs, with future plans to recognize symbols of hate and violence.
With a product team of four, Mike was able to launch Photobucket’s new content moderation workflow using Clarifai in 12 weeks from concept to internal rollout of the new moderation workflow process. With the new workflow increasing productivity for the human moderation team, 80% of Photobucket’s human moderation team was able to transition to full-time customer support.