AI Conclave Online

Speakers:
Rick Sears, Director, Data Processing & Experience, AWS
Luke Anderson, Managing Director, Data & AI, APJ, AWS
Sundar VG, Director, India Specialist, AWS India
Vasant Rao, Managing Director, IDC India

This session explores the current landscape, capabilities, and evolution of Amazon's fully managed service for building generative AI applications. This comprehensive overview examines how Amazon Bedrock serves as a foundation for accessing leading foundation models from various AI companies through a single API. In this session we will also look into security, compliance, real world implementation examples and use cases. This state of the union session provides valuable insights for developers, architects, and business leaders looking to leverage Amazon Bedrock for building and scaling AI-powered applications while maintaining control over their data and costs.

Speaker:
Aparajithan Vaidyanath, Principal Solutions Architect, AWS India

In this session we will talk about how you can get AWS services to get insights from documents, images, audio and video quickly accurately at scale. We will also discuss how developers can customize their output based on their app requirements, specifying the structure, format, and content.

Speaker:
Rahul Sureka, Solutions Architect, AWS India

Agents for Amazon Bedrock automates repetitive and complex tasks by executing multistep workflows, helping improve productivity. In this session, we will cover new features like memory retention, code interpretation and multi-agent collaboration.You will also learn how Agents for Amazon Bedrock can transform your generative AI journey and drive business results.

Speaker:
Sahil Verma, Senior GTM Specialist Solutions Architect, Generative AI, AWS India

In this session, learn how to build scalable and intelligent generative AI applications using Amazon Bedrock, LangChain, and LangGraph. You will learn how to use Amazon Bedrock capabilities with LangChain to process and generate text, images, and data, enabling autonomous agents that understands natural language instructions. In this session, you will also learn how to bring open weight models to Bedrock using custom model import feature. Then, discover how to use the Amazon Bedrock Converse API to build conversational AI agents for streamlined customer service. Finally, you will understand how to integrate Amazon Bedrock with LangGraph to create multistep, AI-powered workflows that adapts to business requirements.

Speaker:
Vatsal Shah, Principal Solutions Architect, AWS India

This session guides you through building an generative AI assistant using an advanced Retrieval Augmented Generation (RAG) technique powered by Amazon Bedrock. We will discuss how to use model evaluations to evaluate the performance and effectiveness of Amazon Bedrock models. You can create automatic model jobs to view performance metrics such as the semantic robustness of a model.

Speaker:
Shailesh Shivakumar, Senior Solutions Architect, AWS India

Amazon SageMaker allows data scientists and ML engineers to accelerate their generative AI journeys by deeply customizing publicly available foundation models (FMs) and deploying them into production applications. The journey begins with Amazon SageMaker JumpStart, an ML hub that provides access to hundreds of publicly available FMs, such as Llama 3, Falcon, and Mistral. Join this session to learn how you can evaluate FMs, select an FM, customize it with advanced techniques, and deploy it—all while implementing AI responsibility, simplifying access control, and enhancing transparency.

Speaker:
Sudhanshu Hate, Principal Solutions Architect, AWS India

Amazon Aurora DSQL is a serverless distributed SQL database with multi-Region active-active capabilities. With its active-active distributed architecture, Aurora DSQL ensures strong data consistency designed for 99.99% single-region and 99.999% multi-region availability. Its serverless design eliminates the operational burden of patching, upgrades, and maintenance downtime. In this session, learn how active-active architecture in Aurora DSQL delivers single- and multi-region resiliency and virtually unlimited scale.

Speaker:
Nethravathi Muddarajaiah, Principal Database Specialist Solutions Architect, AWS India

This session addresses how Amazon Sagemaker Lakeshouse solves data silo challenges by offering a flexible platform that enables in-place data access and querying using Apache Iceberg-compatible tools. The session covers strategies for data source integration, governance implementation, near real-time zero-ETL integrations for operational databases and federated query capabilities for third-party sources within the Lakehouse architecture.

Speaker:
Dipayan Sarkar, Analytics Specialist Solutions Architect, AWS India

Caching is at the heart of any modern application. Amazon ElastiCache is a fully managed Valkey, Memcached and Redis OSS compatible service that delivers real-time, cost-optimized performance for these modern applications. Attend this session to learn how ElastiCache speeds up database and application performance, scaling to millions of operations per second with microsecond response time while offering enhanced security and reliability.

Speaker:
Kanwar Nain Singh, Senior Database Specialist Solutions Architect, AWS India

As you build a data & AI platform on AWS leveraging the modern data architecture, enabling your users with the right amount of access to your data is critical. Attend this session to learn how you can address fundamental challenges such as discovering assets, establishing fine grained access model, deploying necessary governance controls for data lineage and data quality, and promoting collaboration across your organization using next generation Amazon SageMaker. In this session, we will also walk you through the various personas such as a data steward, data engineer and a data analyst, and show you how the next generation Amazon SageMaker makes the user experience more seamless.

Speaker:
Sai Sriparasa, Analytics Specialist Solutions Architect, AWS India

Amazon Aurora provides unparalleled high-performance and availability at global scale with full MySQL and PostgreSQL compatibility, at 1/10th the cost of commercial databases. Amazon Aurora read replicas allows you to increase the read capacity of your Aurora cluster beyond the limits of what a single database instance can provide. Now, Aurora Limitless Database scales write throughput and storage capacity of your database beyond the limits of a single Aurora writer instance. In this session, learn how you can focus on building high-scale applications with Aurora Limitless Database without having to build and maintain complex solutions for scaling your data across multiple database instances to support your workloads.

Speaker:
Deep Dey, Database Specialist Solutions Architect, AWS India

Apache Iceberg is one of the most popular open table formats leveraged for Analytics workloads. Amazon S3 Tables deliver the first cloud object store with built-in Apache Iceberg support and streamline storing tabular data at scale. S3 Tables deliver up to 3x faster query performance and up to 10x higher transactions per second compared to self-managed Iceberg tables stored in general purpose S3 buckets, making them specifically optimized for analytics workloads. Join us for this session to understand how you could improve performance and lower your overheads with S3 Tables.

Speaker:
Ninad Phatak. Senior Manager, Data Solutions Architects, AWS India

Join us for an insightful re:Invent 2024 Recap session, where we'll dive into the latest announcements and innovations from AWS. Gain valuable insights from our experts as they cover game-changing services like Amazon Nova, Amazon Bedrock, Amazon SageMaker Lakehouse, Data Lake 2.0 and more. Don't miss this opportunity to stay ahead of the curve in the ever-evolving cloud computing landscape.

Speaker:
Vijay Srinivasan, Senior Manager, Solutions Architects, AWS India

In this insightful session, explore the cutting-edge world of generative AI and discover how to harness the capabilities of Large Language Models (LLMs), AI Agents, and Agentic Workflows to build powerful and intelligent applications.

Speaker:
Ganesh Balkumar, Senior Solutions Architect, AWS India

This talk outlines essential strategies for preparing data for generative AI, focusing on ensuring data quality through processes like cleaning, labeling, and integration etc.

Speaker:
Madhavi Watve, Senior Solutions Architect, AWS India

As generative AI application gains popularity for building AI applications, effective monitoring and ethical use become essential. This session explores how to leverage Amazon CloudWatch for comprehensive observability of Bedrock-powered applications and introduces Guardrails for responsible AI implementation.

Speaker:
Shibu Jacob, Senior Solutions Architect, AWS India

This forward-looking talk explores the emerging trend of small language models (SLMs) and their potential to revolutionize domain-specific AI applications. Attendees will gain insights into the future of AI, focusing on:
The advantages and applications of SLMs in various industries. Practical examples of building and deploying domain-specific SLMs using Amazon SageMaker and scaling with Amazon Bedrock .Cutting-edge use cases, including: Code interrogation and generation for internal codebases, Reinforcement learning with human feedback (RLHF) for in-vehicle voice assistants.

Speaker:
Pavan Kumar Rao Navule, Solutions Architect, AWS India 

Generative AI is transforming how independent software vendors (ISVs) think about their businesses. In this session, see how a wide range of ISVs use generative AI technologies to improve their operations and enhance their products. Get a sense of where most ISVs are today on the adoption curve, explore the considerations of adopting generative AI in your business, and learn about AWS programs to support your generative AI journey.

Speaker:
Kamal Manchanda, Senior Solutions Architect, AWS India