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Browser AI assistant for reading, analyzing, and generating text within web pages

A desktop work log tool that captures thoughts and decisions while maintaining a knowledge graph.

Road maintenance robot that automatically detects and seals asphalt cracks

PDF information processor that extracts content to generate summaries, tables of contents, and answer targeted questions.

An academic writing assistant platform supporting reading, writing, citation, and multilingual content generation.

Audio and video transcription tool that converts content into summaries, mind maps, and key Q&A.

GTS.ai specializes in providing comprehensive data collection and annotation services for machine learning applications. Their offerings include extensive datasets in image, video, audio, and text formats, designed to meet the specific requirements of AI development projects. With a global team and strict adherence to data privacy standards such as HIPAA and GDPR, GTS.ai ensures that data is sourced securely, accurately, and ethically. Their services support a wide range of industries by delivering customized datasets that enhance model training and performance.

Lunit develops professional software solutions that improve cancer diagnosis and treatment through high-precision analysis of medical images. Its products cover chest X-rays, mammography, and histopathology slide analysis, helping clinicians detect cancer earlier and identify patients who may benefit from immunotherapy. Lunit's tools are clinically validated, FDA-cleared, and integrated into hundreds of healthcare institutions worldwide, providing radiologists and pathologists with faster and more reliable assessment support.

CVAT (Computer Vision Annotation Tool) is a comprehensive data annotation platform designed to streamline the process of creating labeled datasets for machine learning and computer vision applications. The platform provides teams with an intuitive interface and powerful annotation capabilities to handle projects of any scale, from small initiatives to enterprise-level datasets. CVAT supports multiple annotation types, including bounding boxes, polygons, keypoints, skeletons, cuboids, and trajectories, enabling users to prepare data for a wide range of machine learning tasks. By integrating semi-automated annotation tools and supporting major cloud storage providers, CVAT accelerates annotation workflows while maintaining data privacy and security.

Landing AI, founded by AI pioneer Andrew Ng, focuses on visual AI solutions and drives industry transformation by unlocking the value of visual data. Its flagship product, LandingLens, is a cloud-based computer vision platform that enables users to rapidly build, train, and deploy deep learning models for defect detection, classification, and segmentation—regardless of their AI expertise. The platform emphasizes data quality and consistency through advanced annotation tools and a data-centric AI approach, helping enterprises quickly move AI projects from proof of concept to large-scale production. Landing AI supports flexible deployment options, including cloud, edge devices, and integration with third-party platforms such as Snowflake, making it suitable for operations of all scales—from a single production line to global deployments.

Monocle, developed by Brilliant Labs, offers a range of open-source wearable augmented reality devices, including the compact Monocle and Frame smart glasses. These devices feature high-fidelity optics, color OLED displays, integrated cameras, microphones, and FPGA acceleration to support machine learning and computer vision tasks. Designed for developers, hackers, and creatives, Monocle fosters a community-driven ecosystem with accessible hardware and software, enabling users to freely create, customize, and explore AI-enhanced AR applications. The platform supports Bluetooth connectivity, a MicroPython-based operating system, and a comprehensive suite of development tools, empowering innovation in AR experiences.

Segments.ai is a professional data annotation platform designed to streamline the labeling workflow for machine learning teams working with multimodal sensor data. The platform supports simultaneous annotation of 2D images and 3D point clouds, offering advanced automation, batch processing, and an integrated 2D-3D interface. With features such as merged point cloud mode, automatic tracking, and customizable workflows, Segments.ai accelerates the creation of high-quality training datasets, reduces manual effort, and ensures consistent object tracking across modalities and time. Its robust API and Python SDK enable seamless integration into existing data pipelines, making it the platform of choice for robotics, autonomous vehicles, and other sensor-rich industries.