Protect your AI applications and agents from attacks, fakes, unauthorized access, and malicious data inputs.
Control your GenAI applications and agents and assure their alignment with their business purpose.
Proactively test GenAI models, agents, and applications before attackers or users do
The only real-time multi-language multimodality technology to ensure your brand safety and alignment with your GenAI applications.
Ensure your app is compliant with changing regulations around the world across industries.
Proactively identify vulnerabilities through red teaming to produce safe, secure, and reliable models.
Detect and prevent malicious prompts, misuse, and data leaks to ensure your conversational AI remains safe, compliant, and trustworthy.
Protect critical AI-powered applications from adversarial attacks, unauthorized access, and model exploitation across environments.
Provide enterprise-wide AI security and governance, enabling teams to innovate safely while meeting internal risk standards.
Safeguard user-facing AI products by blocking harmful content, preserving brand reputation, and maintaining policy compliance.
Secure autonomous agents against malicious instructions, data exfiltration, and regulatory violations across industries.
Ensure hosted AI services are protected from emerging threats, maintaining secure, reliable, and trusted deployments.
GenAI is evolving faster than the safeguards meant to contain it. From deepfakes to synthetic abuse, the risks are no longer theoretical, and the cost of inaction is rising.ย
In this practical guide, ActiveFence distills frontline insights from working with top AI developers to help enterprise leaders move from principles to practice.ย
Whether you’re scaling LLMs or deploying multimodal agents, this report lays out how to operationalize real-world safety.
In this report, we cover:
Build trust into your AI stack.
Learn how with our practical guide.
Learn how bad actors exploit Agentic AI and discover mitigation strategies.
See why AI safety teams must apply rigorous testing and training with diverse organic and synthetic datasets.
Watch the webinar to explore essential AI safety strategies, including red teaming to identify vulnerabilities, making informed build vs. buy decisions, and leveraging hybrid approaches for scalable solutions.