Embedded BDI provides a full BDI lifecycle engine: it models an agent’s beliefs about its environment, manages evolving desires or goals, selects intentions from a library of plans, and executes behaviors in real time. The framework includes modules for belief base storage, plan library definition, event triggering, and concurrency control tailored for memory-limited microcontrollers. With a simple API, developers annotate beliefs, specify desires, and implement plans in code. Its scheduler handles priority-based intention execution and integrates with hardware interfaces for sensors, actuators, and network communication, making it ideal for autonomous IoT devices, mobile robots, and industrial controllers.

Agenite is a Python-centric AI agent framework designed to streamline the creation, orchestration, and management of autonomous agents. It offers modular components such as memory stores, task schedulers, and event-driven communication channels, enabling developers to build agents capable of stateful interactions, multi-step reasoning, and asynchronous workflows. The platform provides adapters for connecting to external APIs, databases, and message queues, while its pluggable architecture supports custom modules for natural language processing, data retrieval, and decision-making. With built-in storage backends for Redis, SQL, and in-memory caches, Agenite ensures persistent agent state and enables scalable deployments. It also includes a command-line interface and JSON-RPC server for remote control, facilitating integration into CI/CD pipelines and real-time monitoring dashboards.