Saga provides a flexible architecture for building AI agents that plan and execute multi-step workflows. Core components include a planner module that breaks goals into actions, a memory store for conversational and task context, and a tool registry for integrating external services or scripts. Agents run asynchronously, manage state across sessions, and support custom tool development. Saga enables rapid prototyping of autonomous assistants, automating tasks such as data collection, alerting, and interactive Q&A within your own Python environment.

Bedrock Engineer provides developers with a structured, modular way to build AI agents leveraging AWS Bedrock foundation models like Amazon Titan and Anthropic Claude. The toolkit includes example workflows for data retrieval, document analysis, automated reasoning, and multi-step planning. It manages session context, integrates with AWS IAM for secure access, and supports customizable prompt templates. By abstracting away boilerplate code, Bedrock Engineer accelerates development of chatbots, summarization tools, and intelligent assistants, while offering scalability and cost optimization through AWS-managed infrastructure.

Minerva is an extensible AI agent framework designed to automate complex workflows using large language models. Developers can integrate external tools—such as web search, API calls, or file processors—define custom planning strategies, and manage conversational or persistent memory. Minerva supports both synchronous and asynchronous task execution, configurable logging, and a plugin architecture, making it easy to prototype, test, and deploy intelligent agents capable of reasoning, planning, and tool use in real-world scenarios.