Build a protein research copilot with Amazon Bedrock AgentCore

This article presents a technical guide on building a protein research copilot using Amazon Bedrock AgentCore, which enables researchers to search for structurally similar peptides across large datasets using natural language queries. The system combines natural language query parsing, vector similarity search over protein embeddings, and AI-generated scientific summaries of search results. The copilot is built using the Strands Agents SDK and deployed to Amazon Bedrock AgentCore for production serving. The practical implication for engineers building AI systems is the ability to create conversational interfaces that can handle complex research workflows and provide accurate results.

⚡ Key Takeaways

• The system uses the Strands Agents SDK to orchestrate three specialized tools within one agent.
• The copilot deploys to Amazon Bedrock AgentCore for production serving and stores peptide embeddings in Amazon Aurora PostgreSQL-Compatible Edition with pgvector.
• The system uses a custom ML model (ESM-C 300M) as an Amazon SageMaker AI serverless endpoint with bundled weights for fast cold starts.
• The copilot combines vector similarity search (pgvector on Amazon Aurora PostgreSQL) with metadata filtering in a single query.
• The system orchestrates multiple specialized tools, including nested LLM agents, within a single Bedrock AgentCore runtime.

This article provides a concrete example of how to build a conversational AI system that can handle complex research workflows, which can be applied to various domains beyond protein research. The use of Amazon Bedrock AgentCore and Strands Agents SDK enables engineers to create scalable and efficient AI systems.

✅ Practical Steps

1. Install the bedrock-agentcore-starter-toolkit using pip (pip install bedrock-agentcore-starter-toolkit).
2. Deploy a custom ML model (ESM-C 300M) as an Amazon SageMaker AI serverless endpoint with bundled weights for fast cold starts.
3. Use the Strands Agents SDK to orchestrate multiple specialized tools within a single Bedrock AgentCore runtime.

Want the full story? Read the original article.