Wipe out human errors & biases from your influencer review process for Brand Safety

While other AI models for content review are built on LLMs that read the content, they often miss the context. Our model is trained to understand context, meaning it can tell a meme from a safety threat. This offers a human-like interpretation of content, without the errors & biases.

Beyond checking for GARm specified safety categories like violence, hate speech, nudity, symbols or visual attributes, our AI model can also scan for any topic or theme of your choice. This means you can check an influencer’s views on the fashion industry, abortion, political comments, reviews of retail products, and more.

If you want to identify an influencer's take on ongoing trends, fashion & skincare, veganism, or any political stance, you simply need to input the topic/theme into the system. Our model considers the keywords, similar phrases, synonyms, etc to scan and flag all mentions of these specified topics. Please note, this functionality is only supported for paid reports

Other players in the online content review space only offer a limited safety check for an influencer’s profile by reviewing the top content or most latest content, often scanning only 20-30 content pieces. This means scores have a strong recency bias, and the past content gets completely ignored. With Phyllo’s Brand Safety APIs, the AI reads content spanning back over 7 years, and even farther back if specified.

Phyllo's Brand Safety model offers multimodal content scanning. While other solutions are limited in their review capabilities, only scanning text and image content, as their models are built for rudimentary content. Ours extends to audio, video, and even text caption overlays on media - meaning no part of a post gets left behind in the review.