Sabrina Engling
AI Lead @Trusted Shops SE | AWS Community Builder for AI Engineering
Oldenburg, Germany
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Sabrina Engling leads the AI Solutions Team at Trusted Shops and drives AI adoption and innovation across the entire company. Her focus is on scalable AI solutions, AI operations, and agentic commerce. She combines technical expertise with strategic business acumen, bringing together both perspectives - from the architecture of scalable AI systems to business value.
Beyond her corporate role, Sabrina is a dedicated advocate for tech education and serves as Chairwoman of the NGO TechLabs, helping thousands of people build digital skills. As an AWS Commmunity Builder for AI Engineering, alumna of the AWS She Builds mentoring program, a certified AI Manager, and a recent AI hackathon winner, she is committed to empowering more women to take the leap into AI and cloud technologies.
Area of Expertise
Topics
Beyond authentication: an open-source trust model for the agentic web
Authenticating an agent tells you who it is, but not whether to let it transact, access data, or act on a user's behalf. As autonomous agents begin crossing organisational boundaries, the systems they reach face a binary choice: block all agent traffic or accept it without verification - neither of which scales as agent traffic grows.
TSAI (Trust Signals for Agentic Interactions) is an open source protocol that fills this gap. Built on W3C Verifiable Credentials and Decentralised Identifiers (DIDs), it carries trust signals beyond identity - reputation, economic stake, authorization, and endorsements - in cryptographically signed credentials that any system can verify offline. Independent Trust Authorities issue them and agents present them when accessing a service, while receiving systems make their own access decisions based on the signals. Credentials describe the agent, not the user, which preserves user privacy and keeps existing user authentication unchanged.
In this talk, we walk through the architecture - the four-tier trust model that scales from offline verification at low risk to real-time checks at high stakes, the credential format and lifecycle, and how TSAI composes with agent protocols like MCP and A2A. TSAI is developed by AWS and Trusted Shops, combining agent infrastructure expertise with decades of online trust certification.
AI-Powered Customer Support Automation at Trusted Shops with Amazon Bedrock
In this session, I will present the development of our email automation for customer support at Trusted Shops using Amazon Bedrock, from simple LLM API calls to a multi-agent architecture.
We started small: a single Bedrock API call for intent classification, predefined response templates, and a strong focus on data privacy compliance from the very beginning.
Over time, the solution evolved through several stages: from basic prompt engineering to Bedrock Agents, from single-agent to multi-agent orchestration, and finally to Amazon Bedrock AgentCore. Each phase brought new challenges and new learnings about what it takes to run AI solutions in production.
I will also share practical lessons learned along the way, including where simple LLM approaches reach their limits and when agent-based architectures start to add real value.
Today, we can handle over 50% of 1st level support tickets entirely with AI, reduce resolution time by 60%, and continue to achieve high customer satisfaction.
The audience will gain insights into iterative AI implementations, quality control mechanisms and data privacy considerations while keeping customer satisfaction and strengthening the operational service teams.
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