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Explainable AI for customer service on AWS

Customer support is evolving beyond simple chatbots to intelligent, explainable decision layers that enhance efficiency and safety. In this session, we’ll show how AI running on AWS can validate workflows, detect sensitive cases and prevent policy bypass attempts.

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Agenda

  1. Introduction to AI-driven automation for customer support
  2. Business context and challenges
  3. Workflow validation and escalation logic in action
  4. Architecture overview: explainable decision layer on AWS
  5. Lessons learned from production deployments

Key topics

  • how explainable AI improves customer support beyond traditional chatbots;
  • identifying sensitive and high-priority cases and routing them to human agents;
  • verifying customer contact flow with automated best‑path recommendations;
  • preventing workflow bypass and reducing fake engagements to protect policy integrity.

Speaker

Jakub Forysiak

Jakub Forysiak

AI Technical Lead

Jakub leads AI projects end to end – from first concept to production. His role is to bridge strategy and engineering, architecting solutions that combine clean design with robust performance. Whether it’s Generative AI, workflow automation, or advanced decision systems, his focus is the same: solutions that scale, perform, and hold up in the real world.

Amazon Bedrock

Amazon Bedrock

The platform for secure and private Generative AI services

Enter the world of generative AI with Amazon Bedrock — a fully managed service offering top of the line foundation models, including Amazon's own AI model lineup.

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

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