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Autonomous mobility service enabling driverless operation on urban roads

An open-source hardware platform offering sensors, communication modules, and edge computing devices for prototyping.

A computer vision development platform for managing datasets, training models, and deploying inference services.

Browser extension that automatically captures screen activity and logs to generate defect reports

A developer productivity platform supporting structured code reviews and incremental change management

A machine data analytics platform that collects, indexes, and visualizes multi-source log data

Defined.ai specializes in providing comprehensive AI training data and annotation services to enhance the accuracy and reliability of machine learning models. The platform operates the largest ethical AI data marketplace, offering diverse datasets in speech, text, image, and video formats. By combining human intelligence with advanced technology, Defined.ai ensures data cleanliness, reduces bias, and complies with privacy standards. Its services support the training, evaluation, and refinement of AI models, enabling businesses to deploy AI solutions efficiently and responsibly.

Astra AI is an advanced AI solution integrating heterogeneous computing chips and a multimodal AI framework, specifically designed to handle complex AI tasks involving images, speech, text, and video. It supports large-scale AI models and delivers a unified software experience across multiple platforms. With a scalable architecture and extensive partner ecosystem, Astra AI is suitable for a wide range of applications such as smart retail, security, industrial inspection, and multimedia interaction, enabling real-time analysis and intelligent decision-making at the edge.

Encord is an all-in-one AI data platform designed to efficiently support the collection, annotation, and management of diverse data types, including images, video, audio, text, and medical data. The platform enables complex workflows such as multimodal annotation, active learning, and model evaluation, empowering AI teams to build high-quality datasets efficiently. With integrated AI-assisted annotation, customizable workflows, and advanced data management tools, Encord reduces manual effort and accelerates the AI development lifecycle.

Surge AI is a cutting-edge data annotation platform designed to help AI developers, data scientists, and enterprises build powerful and accurate training datasets for machine learning and language model training. Backed by a global team proficient in over 40 languages and powered by AI-assisted quality control, Surge AI ensures high data precision. The platform offers an intuitive interface, customizable workflows, and seamless integration via modern APIs, enabling efficient management of diverse AI application projects such as content moderation, sentiment analysis, search evaluation, and GPT fine-tuning.

FuriosaAI specializes in next-generation AI accelerators, delivering exceptional throughput and energy efficiency for deploying large language models (LLMs) and computer vision applications in enterprise and cloud environments. Its flagship product, RNGD, features a unique tensor contraction processor architecture that maximizes computational and memory efficiency, enabling low-latency, high-throughput inference while reducing power consumption. The hardware is tightly integrated with a comprehensive software stack, including compiler, runtime, and performance analysis tools, to optimize model deployment and scalability in modern data center infrastructures.

Lightly focuses on intelligent data selection and management within machine learning workflows, aiming to reduce redundancy and bias while improving model accuracy. It leverages self-supervised and active learning techniques to identify the most relevant and diverse subsets of data, enabling faster and more efficient model training. The platform integrates with cloud storage and supports automation through APIs and SDKs, including an edge device SDK for real-time data filtering. Lightly's tools help teams scale data management, gain insights into data distributions, and streamline the annotation process.