Council provides a structured environment for designing AI agents by defining roles, chaining tasks, and integrating external tools or APIs. Users can configure memory stores, manage agent state, and implement custom reasoning pipelines. Council’s plugin architecture allows seamless integration with NLP services, data sources, and third-party tools, enabling you to rapidly prototype and deploy multi-agent systems that coordinate to perform complex tasks reliably.

LLMWare serves as a comprehensive toolkit for constructing AI agents powered by large language models. It allows you to define reusable chains, integrate external tools via simple interfaces, manage contextual memory states, and orchestrate multi-step reasoning across language models and downstream services. With LLMWare, developers can plug in different model backends, set up agent decision logic, and attach custom toolkits for tasks like web browsing, database queries, or API calls. Its modular design enables rapid prototyping of autonomous agents, chatbots, or research assistants, offering built-in logging, error handling, and deployment adapters for both development and production environments.

Drive Flow is a flexible framework that empowers developers to design AI-powered workflows by defining sequences of steps. Each step can invoke large language models, execute custom functions, or interact with persistent memory stored in MemoDB. The framework supports complex branching logic, loops, parallel task execution, and dynamic input handling. Built in TypeScript, it uses a declarative DSL to specify flows, enabling clear separation of orchestration logic. Drive Flow also provides built-in error handling, retry strategies, execution context tracking, and extensive logging. Core use cases include AI assistants, automated document processing, customer support automation, and multi-step decision systems. By abstracting orchestration, Drive Flow accelerates development and simplifies maintenance of AI applications.