OpenAI Autogen Dev Studio is a desktop web application designed to streamline the end-to-end development of AI agents built on the OpenAI Autogen framework. It offers a visual, conversation-centric interface where developers can define system prompts, configure memory strategies, integrate external tools, and adjust model parameters. Users can simulate multi-turn dialogues in real time, inspect generated responses, trace execution paths, and debug agent logic within an interactive console. The platform also includes code scaffolding features to export fully-functional agent modules, enabling seamless integration into production environments. By centralizing workflow automation, debugging, and code generation, it accelerates prototyping and reduces development complexity for conversational AI projects.

PersonifAI is an innovative AI platform where you can design and customize AI personas for various purposes, including storytelling, automation, and real-time simulation. Engage in one-on-one or group interactions, create immersive storytelling experiences, automate AI tasks with custom workflows, and test your ideas through dynamic simulations. Whether you're a creator, professional, or an AI enthusiast, PersonifAI offers tools to make AI personal, accessible, and endlessly customizable.

LightJason Benchmark offers a comprehensive set of predefined and customizable scenarios to stress-test and evaluate multi-agent applications built on the LightJason framework. Users can configure agent counts, communication patterns, and environmental parameters to simulate real-world workloads and assess system behavior. Benchmarks gather metrics such as message throughput, agent response times, CPU and memory consumption, logging results to CSV and graphical formats. Its integration with JUnit allows seamless inclusion in automated testing pipelines, enabling regression and performance testing as part of CI/CD workflows. With adjustable settings and extensible scenario templates, the suite helps pinpoint performance bottlenecks, validate scalability claims, and guide architectural optimizations for high-performance, resilient multi-agent systems.