Proactively identify vulnerabilities through red teaming to produce safe, secure, and reliable models.
Deploy generative AI applications and agents in a safe, secure, and scalable way with guardrails.
Identify safety gaps early and mitigate them quickly to ensure your models are safe, aligned, and compliant.
AI has democratized content creation – enabling anyone to create media – both legitimate and unwanted. As new models are released to the public – their potential misuse creates legal and brand risks that foundation models cannot afford to take.
Obtain full visibility of known and unknown content risks in your model with proactive testing that mimics unwanted activity to detect safety gaps.
Fine-tune and optimize your models with labeled datasets that support DPO & RLHF processes to actively mitigate safety gaps.
ActiveFence’s proactive AI safety is driven by our outside-in approach, where we monitor threat actors’ underground chatter to study new tactics in AI abuse, rising chatter, and evasion techniques. This allows us to uncover and respond to new harms before they become your problem.
Tomer Poran
ActiveFence
Guy Paltieli, PhD
Tomomi Tanaka, PhD
Design Lab
Yoav Schlesinger
Salesforce
Discover expert insights on building AI safety tools to tackle evolving online risks and enhance platform protection.
Master GenAI safety with our latest Red Teaming Report: Strategies, case studies, and actionable advice
We tested AI-powered chatbots to see how they handle unsafe prompts. Learn how they did, and how to secure your AI implementation.