A financial services team spends significant time each week manually creating client PowerPoint presentations from quarterly reports, compliance documents, and market analyses. Each presentation requires reading hundreds of pages, extracting key data points, structuring slides, and generating supporting visuals. This post walks you through building an AI agent system using Amazon Bedrock AgentCore that automates this workflow, completing in under 90 seconds in our internal testing. This approach reduces presentation creation time while grounding content in source documents. The solution deploys a supervisor agent on AgentCore runtime, a capability of Amazon Bedrock AgentCore, using the Strands Agents framework to orchestrate document generation and summarization tools. Anthropic Claude Sonnet 4.6 (available on Amazon Bedrock) handles content creation, Amazon Titan Text Embeddings v2 powers vector search, and Stability AI Stable Image Inpaint (available on Amazon Bedrock) generates slide images. This post includes a public repository with the code assets.
The solution deploys a single supervisor agent on Amazon Bedrock AgentCore runtime that selects between document generation and summarization tools based on user requests. A Retrieval Augmented Generation (RAG) pipeline uses Amazon OpenSearch Serverless for vector storage and semantic search across multimodal content.
NET 8 minimal APIs, so you can integrate with existing enterprise applications through standard HTTP calls. AWS Lambda offers serverless compute, including containerized functions for PowerPoint generation. The solution secures the implementation with Amazon Virtual Private Cloud (Amazon VPC) isolation, AWS Key Management Service (AWS KMS) encryption, and AWS Identity and Access Management (IAM) least-privilege access control.
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