AgentSmithy is designed to streamline the development lifecycle of AI agents by offering modular components for memory management, task planning, and execution orchestration. The framework leverages Google Cloud Storage or Firestore for persistent memory, Cloud Functions for event-driven triggers, and Pub/Sub for scalable messaging. Handlers define agent behaviors, while planners manage multi-step task execution. Observability modules track performance metrics and logs. Developers can integrate bespoke plugins to enhance capabilities such as custom data sources, specialized LLMs, or domain-specific tools. AgentSmithy’s cloud-native architecture ensures high availability and elasticity, allowing deployment across development, testing, and production environments seamlessly. With built-in security and role-based access controls, teams can maintain governance while rapidly iterating on intelligent agent solutions.

Lamini is a specialized enterprise platform that allows software teams to create, manage, and deploy large language models (LLMs) with ease. It provides comprehensive tools for model development, refinement, and deployment, ensuring that every step of the process is integrated seamlessly. With built-in best practices and a user-friendly web UI, Lamini accelerates the development cycle of LLMs, enabling companies to harness the power of artificial intelligence efficiently and securely, whether deployed on-premises or on Lamini's hosted GPUs.

Ardor is an advanced platform for automating the software development lifecycle (SDLC). It enables users to build, deploy, and scale AI agentic applications on the cloud quickly. With a streamlined process, Ardor simplifies complex development tasks, reducing time to market and cutting down on costs. Users describe their ideas in natural language, and Ardor’s AI capabilities take care of the development, deployment, and optimization processes. The platform is designed to handle everything from architecture design to scaling, making it an all-encompassing solution for modern software development.

The Java AgentSpeak Consistency Checker loads AgentSpeak source files, analyzes belief bases, goal definitions, and plan structures, then runs a suite of consistency and validity tests. It identifies conflicting plans, unreachable goals, and inconsistent belief updates, generating detailed reports. By integrating into build processes or CI pipelines, it helps developers catch design flaws early, maintain robust BDI agents, and accelerate multi-agent application development.