SafetyKit’s agents leverage GPT‑5, GPT‑4.1, deep research, and Computer Using Agent (CUA) to review 100% of customer content with over 95% accuracy based on SafetyKit’s evals. They can help platforms protect users, prevent fraud, avoid regulatory fines and enforce complex policies that legacy systems may miss, such as region-specific rules, embedded phone numbers in scam images, or explicit content. Automation can also protect human moderators from exposure to offensive material and frees them to handle nuanced policy decisions.

SafetyKit’s agents are each built to handle a specific risk category, from scams to illegal products. Every piece of content is routed to the agent best suited for that violation, using the optimal OpenAI model:

This model-matching approach lets SafetyKit scale content review across modalities with more nuance and accuracy than legacy solutions can.

The Scam Detection agent, for example, goes beyond just scanning text. It analyzes visuals like QR codes or phone numbers embedded in product images. GPT‑4.1 helps it parse the image, understand the layout, and decide whether it is a policy violation.