Manage and orchestrate the entire Trust & Safety operation in one place - no coding required.
Take fast action on abuse. Our AI models contextually detect 14+ abuse areas - with unparalleled accuracy.
Watch our on-demand demo and see how ActiveOS and ActiveScore power Trust & Safety at scale.
The threat landscape is dynamic. Harness an intelligence-based approach to tackle the evolving risks to users on the web.
Don't wait for users to see abuse. Proactively detect it.
Prevent high-risk actors from striking again.
For a deep understanding of abuse
To catch the risks as they emerge
Disrupt the economy of abuse.
Mimic the bad actors - to stop them.
Online abuse has countless forms. Understand the types of risks Trust & Safety teams must keep users safe from on-platform.
Stop online toxic & malicious activity in real time to keep your video streams and users safe from harm.
The world expects responsible use of AI. Implement adequate safeguards to your foundation model or AI application.
Implement the right AI-guardrails for your unique business needs, mitigate safety, privacy and security risks and stay in control of your data.
Our out-of-the-box solutions support platform transparency and compliance.
Keep up with T&S laws, from the Online Safety Bill to the Online Safety Act.
Over 70 elections will take place in 2024: don't let your platform be abused to harm election integrity.
Protect your brand integrity before the damage is done.
From privacy risks, to credential theft and malware, the cyber threats to users are continuously evolving.
Here's what you need to know.
The counterfeit industry was worth over $5 billion in 2016, and this figure is only growing. This harmful economy not only harms the businesses of brands with designs stolen and revenue interrupted, but it also can jeopardize consumers who may inadvertently purchase unsafe products. These counterfeit networks promote their operation’s fake and illegal goods by exploiting:
In this case study ActiveFence shows how brands and platforms can secure themselves from intellectual property right infringements using a combination of cross-platform detection, signifier detection, and network analysis to identify whole systems of abuse.