Ango Hub
Ango Hub is a quality-focused, enterprise-ready data annotation platform for AI teams, available on cloud and on-premise. It supports computer vision, medical imaging, NLP, audio, video, and 3D point cloud annotation, powering use cases from autonomous driving and robotics to healthcare AI.
Built for AI fine-tuning, RLHF, LLM evaluation, and human-in-the-loop workflows, Ango Hub boosts throughput with automation, model-assisted pre-labeling, and customizable QA while maintaining accuracy. Features include centralized instructions, review pipelines, issue tracking, and consensus across up to 30 annotators. With nearly twenty labeling tools—such as rotated bounding boxes, label relations, nested conditional questions, and table-based labeling—it supports both simple and complex projects. It also enables annotation pipelines for chain-of-thought reasoning and next-gen LLM training and enterprise-grade security with HIPAA compliance, SOC 2 certification, and role-based access controls.
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AthenaHQ
AthenaHQ is a cutting-edge platform for Generative Engine Optimization (GEO), designed to help brands optimize their visibility and performance across AI-driven search platforms like ChatGPT, Gemini, Perplexity, DeepSeek, Google's AI Overviews, and more. With Athena, companies can monitor AI perception, identify content gaps, and adjust strategies for better AI-driven discovery. AthenaHQ offers features like competitor analysis, sentiment analysis, and AI search volume tracking, making it easier for companies to align with the evolving search ecosystem. By understanding AI’s role in brand discovery, AthenaHQ empowers brands to stay ahead in the rapidly changing AI landscape.
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NVIDIA Isaac Lab
NVIDIA Isaac Lab is a GPU‑accelerated, open source robot learning framework built on top of Isaac Sim, designed to unify and simplify robotics research workflows such as reinforcement learning, imitation learning, and motion planning. It leverages realistic sensor and physics simulation to support accurate training of embodied agents, providing ready‑to‑use environments, spanning manipulators, quadrupeds, and humanoids—with support for 30+ benchmark tasks and integration with popular RL libraries like RL Games, Stable Baselines, RSL RL, and SKRL. Isaac Lab features a modular, configuration‑driven design that enables developers to easily create, modify, and scale learning environments; it also supports collecting demonstrations via peripherals (gamepads, keyboards) and allows custom actuator models to facilitate sim‑to‑real transfer. The framework is built for both local and cloud deployment, accommodating flexible scaling of compute resources.
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