- Goal of the Webinar
- Target Audience & Expectations for the Webinar
Description
The webinar demonstrates how modern AI solutions can be implemented using native AWS infrastructure – from knowledge provisioning and vector search to deterministic agents.
Rather than focusing on a pure technology comparison, it highlights concrete architectures and real-world use cases. Key AWS services like Bedrock, OpenSearch Serverless, and API-based agent solutions will be presented and interactively showcased.
Participants will gain hands-on insights into how these components can be combined – including architectural overviews, code snippets, and evaluations of each service’s suitability for different application scenarios.
The webinar is tailored for technical decision-makers, architects, and developers seeking a solid overview of current options in the AWS ecosystem.
Register
Experts

Lukas Schiffers
Agenda
Introduction
Vector Search with OpenSearch
- Aufbau einer Vektor-Datenbank in AWS inkl. Metadaten-Filter
- AOS Domains vs. Serverless
- Live-Demo: Kategorisierung von Inhalten mittels Vector Search
Chatbots with AWS Bedrock Knowledge Base
- Capabilities & Structure of a Knowledge Base with Bedrock
- Comparison of Different Vector Databases
- Live Demo: Chatbot for HTML-Based Content
-
Agents & API-Integration
- When Rule-Based Agents Make Sense (Potential Use Cases)
- Architecture of a Deterministic Agent
- Live Demo: Integrating an Agent into an Existing Workflow
Q&A & Discussion
- Discussion on Questions, Ideas & Real-World Use Cases
- Overall Overview of the Architecture Used
Basic information
Participants should be familiar with the basics of Retrieval-Augmented Generation (RAG). Experience with AWS, embeddings, and vector search is beneficial. Technical knowledge in Python, Streamlit, or cloud-native architectures is not required, but can help participants better follow the live demos and examples.
Online-Webinar
Cloud Architects, Developers & DevOps, Technical Decision-Makers, and Anyone Interested in LLM/Chatbot Applications in the AWS Environment
German