19.11, WebinarAI guardrails - comparisonRegister now
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AI guardrails tested – a practical comparison

Cloud-native service, SASE network layer, or security platform? During our webinar, we compare three AI security solutions through hands-on tests of attack detection, data leaks, latency, and cost.

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Agenda

  1. Why AI applications need dedicated guardrails
  2. Bots vs agents: what changes for guardrails and monitoring
  3. Three approaches to AI security: an overview
  4. Comparing guardrail capabilities, language support, and integrations
  5. Hands-on testing: attack detection and latency
  6. Key takeaways: choosing the right solution for your use case

Key topics

  • why model-level safety filters are no longer enough when AI applications interact with users, data, and tools;
  • how chatbot security differs from protecting autonomous agents - for both guardrails and monitoring;
  • three AI security approaches tested against the same application: Amazon Bedrock Guardrails, Cato AI Security, and CrowdStrike Falcon Guardian;
  • integration options and their impact on your architecture;
  • real test results: attacks detected and latency added under the same scenario;
  • extra features, deployment models and pricing.

Speaker

Piotr Krawiranda

Piotr Krawiranda

AI Architect

An AI Architect with 10+ years in engineering and 6+ focused on applied AI, he has designed and deployed systems across computer vision, deep learning, MLOps, and cloud-native AI architectures. He bridges research and production, from autonomous ground vehicles to enterprise applications.

Amazon Bedrock

Amazon Bedrock

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Thanks to its serverless design, Amazon Bedrock eliminates the complexity of running AI at scale, and lets you seamlessly integrate agentic AI into your applications using familiar AWS services — whether it's your first steps with AI, or you are already revolutionizing the market.

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