Aeiva is a developer-first platform that enables you to create, deploy, and evaluate autonomous AI agents within flexible simulation environments. It features a plugin-based engine for environment definition, intuitive APIs to customize agent decision loops, and built-in metrics collection for performance analysis. The framework supports integration with OpenAI Gym, PyTorch, and TensorFlow, plus real-time web UI for monitoring live simulations. Aeiva’s benchmarking tools let you organize agent tournaments, record results, and visualize agent behaviors to fine-tune strategies and accelerate multi-agent AI research.

SeeAct is designed to empower vision-language agents with a two-stage pipeline: a planning module powered by large language models generates subgoals based on observed scenes, and an execution module translates subgoals into environment-specific actions. A perception backbone extracts object and scene features from images or simulations. The modular architecture allows easy replacement of planners or perception networks and supports evaluation on AI2-THOR, Habitat, and custom environments. SeeAct accelerates research on interactive embodied AI by providing end-to-end task decomposition, grounding, and execution.

RoboCup Rescue Agent Simulation is an open-source framework that models urban disaster environments where multiple AI-driven agents collaborate to locate and rescue victims. It offers interfaces for navigation, mapping, communication, and sensor integration. Users can script custom agent strategies, run batch experiments, and visualize agent performance metrics. The platform supports scenario configuration, logging, and result analysis to accelerate research in multi-agent systems and disaster response algorithms.

HyperBrowser transforms standard web browsing by embedding generative AI capabilities throughout every online interaction. Users can select any webpage text and instantly receive concise summaries or detailed explanations, ask natural language questions to extract specific information, and automatically generate reports or content drafts. Built-in table and data extraction tools allow seamless acquisition of structured datasets, while integrated code assistance supports developers by generating snippets and debugging. The extension also enables chatbot conversations, PDF summarization, and customizable workflows to automate repetitive tasks such as form filling or social media monitoring. By unifying multiple AI functions in a single interface, HyperBrowser accelerates research, analysis, and content creation, making web navigation smarter and more productive.