Build GenAI application with OpenSearch Serverless

Large language models (LLMs) are impressive, yet they come with several limitations such as hallucination, lack of domain knowledge, temporal constraints, and explainability challenges.In this session i will cover how we can utilize the Amazon OpenSearch serverless to address these limitations and support LLMs in delivering precise and understandable responses.

Vector Search with OpenSearch

How you can improve Search releavance with Amazon OpenSearch vector capabilities. Also look at retrieval-augmented generation and conversation search.

Unlocking the Power of OpenSearch: AI-Powered Assistants for Seamless Data Interaction

In this discussion, we will explore OpenSearch and its diverse use cases. We'll delve into the vibrant OpenSearch community and highlight its cutting-edge features. Additionally, I will demonstrate how to integrate various data sources to bring in logs, metrics, and traces in real time. Once your data is in OpenSearch, visualize data, build anomaly detection, enhance observability, and use AI-powered assistants to interact with your data.

Build GenAI application with OpenSearch Serverless

Large language models (LLMs) are impressive, yet they come with several limitations such as hallucination, lack of domain knowledge, temporal constraints, and explainability challenges.In this session i will cover how we can utilize the Amazon OpenSearch serverless to address these limitations and support LLMs in delivering precise and understandable responses.

Master Your Infrastructure: Advanced Monitoring with OpenSearch Security Analytics, Alerting, AD

In this talk, we'll explore how to automate your infrastructure monitoring with OpenSearch, a powerful, community-driven suite built on Lucene. Learn to consolidate logs, metrics, and traces in one place, set up effective monitoring, use machine learning for anomaly detection, and interact with your data using an AI-powered assistant.

Session : will be presentation and demo
List of conferences(done so far this year) :
1. Reinvent Recap Mancheter , 18-Jan-2024 , 150 Attendees
2. Reinvent Recap London : 8-Feb-2024 , 200 Attendees
3. 4D event Dublin : 16-May-2024 , 50 Attendees
4. AWS Sheffield meet up Event : 12-June-2024 , 50 Attendees

Technical requirement : Presentation screen
Target Audience : DevOps , Application Devlopers , Serverless , platform Engineers , Architects

Session Duration : 45 minutes

Revolutionizing Multimedia Content Search with Vector-Powered Semantic Search

This session explores the transformation of multi media content search, showcasing a case study that leverages OpenSearch and multimodal models to implement semantic search for images and captions. We'll discuss how this advanced approach significantly improves result relevancy and user experience compared to traditional keyword-based systems. Attendees will learn practical strategies for implementing vector search and multimodal models in their own digital asset management systems, potentially revolutionizing visual content discovery across various industries. Gain insights into overcoming common challenges and enhancing search capabilities for more intuitive and efficient user interactions.

target audience : AI/ML engineer , GEN AI application
preferred session duration : 30-40 minutes

Supercharging Search in OpenSearch: Harnessing User Behavior for Continuous Improvement

Organizations invest significant resources in building and optimizing their search systems, relying on OpenSearch to deliver the most relevant results. However, while search queries may return top results, this only tells part of the story. Critical details are often missing—such as which product a user selects, whether they add it to their cart, or if they are satisfied with the results. These insights are vital for improving the search experience, yet they are not captured by the search system itself.

In this session, I will demonstrate how to go beyond basic search results by capturing user behavior, including the specific searches they perform, their interactions with search results, and events such as time spent on the search page and the products they select. By feeding this data into an analytical engine, we can continuously learn from user behavior and adjust the search system accordingly.

This approach gives organizations a complete view of their users' actions, enabling them to understand what works and what doesn’t in the search experience. It helps track essential metrics like how long users stay on the search page, which products catch their attention, and how their interactions align with overall satisfaction. With these insights, organizations can fine-tune search relevance, optimize product recommendations, and ultimately improve the user experience.

To illustrate this process, I will use OpenSearch in an open-source environment, providing a live demo that showcases how these techniques work in practice. By the end of the session, you will have a clear understanding of how capturing user behavior data can drive more relevant search results and enhance the overall user experience in your system.

Capturing user behavior insights in search systems offers numerous benefits, including enhanced search relevance, improved user experience, and continuous system learning. By tracking user interactions—such as which products they select, how long they spend on search pages, and their overall engagement—organizations can fine-tune search algorithms for more personalized and accurate results. This data-driven approach leads to better product discovery, increased conversions, and reduced bounce rates. Additionally, it allows for greater personalization and ongoing optimization, ultimately driving higher customer satisfaction and business growth. In essence, understanding user behavior helps create a smarter, more effective search experience that evolves with user needs.

Ingest, Store, Search, and Analyze Your Data—All Serverless, All Seamless!

In today's rapidly evolving tech landscape, organizations are increasingly turning to serverless technologies to streamline operations, reduce costs, and minimize manual intervention. This session explores how serverless solutions can revolutionize your log management processes, from ingestion and storage to advanced search capabilities. Join us to discover how serverless architectures can efficiently handle log ingestion and storage at scale, while leveraging advanced search techniques including fuzzy search, boosting, and autocomplete to quickly pinpoint specific log entries among millions. We'll examine both native serverless solutions and third-party tools for log analytics and searching, providing strategies for implementing a fully serverless approach to simplify monitoring and improve overall operational efficiency.

Discover how serverless technologies streamline log ingestion, storage, and search. Learn advanced techniques like fuzzy search and autocomplete to quickly find logs. Explore native and third-party tools to enhance monitoring and boost operational efficiency with a fully serverless approach.

Build powerful AI apps using Model Context Protocol

What if connecting AI to your data sources was a seamless plug-and-play experience? That is precisely what Model Context Protocol (MCP) offers! This revolutionary open-source protocol dramatically changes the way AI systems access and work with your data, whether it’s stored in Google Drive, Slack, PostgreSQL databases or elsewhere.

The MCP model provides a universal standard which eliminates the need for countless configuration battles. Think of MCP as a transcendental universal translator that sits between your AI and data infrastructure – now with full interoperability. As a bonus, it is completely open-source and privacy-preserving; enabling agile two-way integration where information flows freely without hindrance.

In this captivating session we explore the wonders of MCP by understanding how it simplifies integrations while simultaneously increasing context awareness at scale. Join em in searching advanced use cases to showcase with you how MCP takes supercharging AI projects from basic functionalities to extraordinary expansions. Everyone from early-stage developers to pros will gain knowledge on harnessing MCP for advanced AI applications catered towards agility and refinement.

Technical requirement : presentation where demo can be shown

Target audience :

Software Developers
AI Engineers
System Architects
API Integration Specialists
Enterprise Solution Architects
Startup Founders and CTOs

List of conferences:

Here's the updated list with the new entry added at the top:

| Date | Event | Artifact | Artifact Link | Action | Notes | Audience |
|------------|-----------------------------------------------------------------------|----------------|---------------|--------------------------------------------------------|-----------------------------------------------------------------------|----------|
| 30-Apr-25 | Break out session London Summit: Build NextGen Search and Conversational AI with Amazon OpenSearch | Link | [Link](https://aws.amazon.com/) | Breakout session | Audience: 1200 | External |
| 15-Oct-24 | Multi-Tenant workloads on OpenSearch - Data and GenAI day London | Link | [Link](https://aws.amazon.com/uki/cloud-services/aws-events/generative-ai-data-day/) | Breakout session | Audience: 250 | External |
| 10-Oct-24 | Semantic search with OpenSearch - AWS Cloud Day Dublin | Link | [Link](https://aws.amazon.com/events/cloud-days/dublin/agenda/) | Presentation | Audience: 200 | External |
| 22-Feb-2025| DDD North - Observability | https://www.dddnorth.co.uk/schedule | [Link](https://www.dddnorth.co.uk/schedule) | Public speaking | 150 attendees, CSAT: Not yet received | External |
| 18-Jan-24 | Zero ETL OpenSearch-DynamoDB - Reinvent Recap Manchester | Link | [Link](https://aws-experience.com/emea/uki/xe/fc6f1/reinvent-recap-manchester) | Public Speaking on Zero ETL integration OpenSearch DynamoDB | Audience: 250, CSAT: 4.9 | External |
| 8-Feb-24 | Vector DB on OpenSearch serverless - Reinvent Recap London | Link | [Link](https://aws-experience.com/emea/uki/xe/5370a/reinvent-recap-london) | Public Speaking on OpenSearch serverless vector capabilities | Audience: 80, CSAT: 4.6 | External |
| 9-Feb-24 | Vector DB on OpenSearch serverless - Reinvent Recap London | Link | [Link](https://aws-experience.com/emea/uki/xe/5370a/reinvent-recap-london) | Public Speaking on OpenSearch serverless vector capabilities | Audience: 70, CSAT: 4.6 | External |
| 16-May-24 | Build serverless RAG workflow using a vector engine - DDD Day Dublin | Link | [Link](https://aws-experience.com/emea/smb/e/57ab4/data-deep-dive-day4ddublin-chapter) | Presentation and Demo | Audience: 50, CSAT: 4.8 | External |
| 12-Jun-24 | Vector Capabilities of OpenSearch - AWS Meetups Sheffield | Link | [Link](https://www.meetup.com/awssheffield/events/301014327/) | Presentation | Audience: 40, CSAT: 4.8 | External |
| 10-Jul-24 | Modernizing and optimizing log analytics with Amazon OpenSearch | Link | [Link](https://aws-experience.com/emea/uki/e/2d54a/modernizing-and-optimizing-log-analytics-with-amazon-opensearch) | Presentation | Audience: 40, CSAT: 4.46, Online Webinar | External |
| 15-Oct-24 | Multi-Tenant workloads on OpenSearch - Data and GenAI day London | Link | [Link](https://aws.amazon.com/uki/cloud-services/aws-events/generative-ai-data-day/) | Breakout session | Audience: 250 | External |
| 10-Oct-24 | Semantic search with OpenSearch - AWS Cloud Day Dublin | Link | [Link](https://aws.amazon.com/events/cloud-days/dublin/agenda/) | Presentation | Audience: 200 | External |
| 3-Oct-24 | Amazon OpenSearch 101 - ISV L&L | Link | [Link](https://aws-experience.com/emea/smb/e/fe0d0/amazon-opensearch-lunch-and-learn---whats-new-with-amazon-opensearch) | Presentation | Audience: 30, CSAT: 4.725 | External |
| 24-Oct-24 | Log Analytics & Observability - ISV L&L | Link | [Link](https://aws-experience.com/emea/smb/e/04520/dive-deep-log-analytics--observability-with-amazon-opensearch-service) | Presentation | 25 attendees, 5 survey responses, CSAT: 4.9 | External |
| 14-Nov-24 | Amazon OpenSearch as VectorDB - ISV L&L | Link | [Link](https://aws-experience.com/emea/smb/e/b96ff/dive-deep-amazon-opensearch-as-vectordb) | Presentation | 20 Attendees, 9 Surveys, CSAT: 5 | External |

This table now includes the new entry at the top.