Swarm Simulator provides a customizable environment for real-time multi-agent experiments. Users can adjust key behavior parameters—alignment, cohesion, separation—and observe emergent dynamics on a visual canvas. It supports interactive UI sliders, dynamic agent count adjustment, and data export for analysis. Ideal for educational demonstrations, research prototyping, or hobbyist exploration of swarm intelligence principles.

Emma-X provides a modular agent orchestration platform for building conversational AI assistants using large language models. Developers can define agent behaviors via JSON configurations, select LLM providers like OpenAI, Hugging Face, or local endpoints, and attach external tools such as search, database, or custom APIs. The built-in memory layer preserves context across sessions, while the UI components handle chat rendering, file uploads, and interactive prompts. Plugin hooks allow real-time data fetching, analytics, and custom action buttons. Emma-X ships with example agents for customer support, content creation, and code generation. Its open architecture lets teams extend agent capabilities, integrate with existing web applications, and quickly iterate on conversation flows without deep LLM expertise.

Morph helps users quickly build AI apps that can be securely deployed with ease. The platform supports connections to data sources like BigQuery and Snowflake, and allows for data processing using OpenAI APIs and ML models in Python. With Morph, you can create interactive screens in Markdown and share them via URLs. Additionally, the framework comes pre-equipped with role-based access control and advanced security features to ensure your data is protected.