List of CVAT.AI Platform Customers
Palo Alto, 94306, CA,
United States
Since 2010, our global team of researchers has been studying CVAT.AI Platform customers around the world, aggregating massive amounts of data points that form the basis of our forecast assumptions and perhaps the rise and fall of certain vendors and their products on a quarterly basis.
Each quarter our research team identifies companies that have purchased CVAT.AI Platform for Image Recognition from public (Press Releases, Customer References, Testimonials, Case Studies and Success Stories) and proprietary sources, including the customer size, industry, location, implementation status, partner involvement, LOB Key Stakeholders and related IT decision-makers contact details.
Companies using CVAT.AI Platform for Image Recognition include: Intel, a United States based Manufacturing organisation with 88400 employees and revenues of $53.10 billion, University of South Carolina, a United States based Education organisation with 1600 employees and revenues of $380.0 million, California Fish Grill, a United States based Leisure and Hospitality organisation with 1200 employees and revenues of $50.0 million and many others.
Contact us if you need a completed and verified list of companies using CVAT.AI Platform, including the breakdown by industry (21 Verticals), Geography (Region, Country, State, City), Company Size (Revenue, Employees, Asset) and related IT Decision Makers, Key Stakeholders, business and technology executives responsible for the software purchases.
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| Logo | Customer | Industry | Empl. | Revenue | Country | Vendor | Application | Category | When | SI | Insight |
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California Fish Grill | Leisure and Hospitality | 1200 | $50M | United States | CVAT.AI | CVAT.AI Platform | Image Recognition | 2023 | n/a |
In 2023, California Fish Grill implemented CVAT.AI Platform to introduce Image Recognition capabilities into its operations. CVAT.AI Platform was deployed to provide image annotation and model lifecycle support typical of the Image Recognition category, aimed at augmenting operational monitoring and visual data workflows.
California Fish Grill integrated CBS NorthStar Order Entry with OSM Solutions' Menuboard Manager to publish menus and pricing automatically across 54 stores, improving menu consistency and reducing manual updates. This menu-management and order-entry operations implementation in the United States went live in 2023 and delivered faster price updates and real-time out-of-stock visibility.
The implementation combined automated menu publishing and pricing distribution with image-driven operational tooling, aligning order entry workflows and menuboard management. Functional scope emphasized menu-management and order-entry operations, with real-time out-of-stock signaling and automated price propagation across the multi-site restaurant footprint of 54 locations.
Governance and process changes focused on centralizing menu publishing and reducing manual update steps, bringing operations and merchandising workflows into a coordinated release cadence. Stated outcomes included improved menu consistency, fewer manual updates, faster price updates, and real-time visibility into out-of-stock conditions.
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Intel | Manufacturing | 88400 | $53.1B | United States | CVAT.AI | CVAT.AI Platform | Image Recognition | 2017 | n/a |
In 2017, Intel implemented the CVAT.AI Platform as an internal data-annotation tool for computer vision R&D in the United States, positioning the deployment within the Image Recognition category to produce large labeled datasets for model training. The CVAT.AI Platform was used by Intel research teams to support dataset curation workflows and to generate training data for CV models at scale.
The implementation emphasized high-volume annotation capabilities, handling hundreds of thousands of objects through centralized annotation workflows, labeling, and quality control orchestration to support iterative model training cycles. Functional usage focused on annotation and R&D modules, with configuration and task orchestration designed to feed downstream model development pipelines.
Intel maintained the platform internally for its computer vision research organization and later contributed the CVAT source to the open-source CVAT project, preserving the same annotation and dataset management patterns. The deployment linked the CVAT.AI Platform, Image Recognition workflows, and Intel research functions, enabling reproducible labeling processes and shared datasets for ongoing CV model development.
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University of South Carolina | Education | 1600 | $380M | United States | CVAT.AI | CVAT.AI Platform | Image Recognition | 2021 | n/a |
In 2021 the University of South Carolina iWERS research group adopted the CVAT.AI Platform for Image Recognition work to create the ATLANTIS benchmark for semantic segmentation of waterbody images as part of an environmental and engineering research project in the United States. The CVAT.AI Platform was applied within research workflows to produce a public dataset that was published in 2022 and explicitly supports model training and evaluation.
Implementation centered on pixel wise annotations and segmentation workflows, with CVAT.AI Platform used for semantic segmentation labeling across the image corpus. Module usage for segmentation workflows is documented in the project repository, indicating systematic use of mask creation, frame level annotation sequencing, and label schema management consistent with semantic segmentation use cases.
Operational scope was research group level, impacting environmental engineering and computer vision research teams at the University of South Carolina, and producing a publicly available ATLANTIS dataset to support downstream model development. There are no named systems integrated in the record, the primary system recorded is the CVAT.AI Platform and the business function is research data labeling for Image Recognition model training and evaluation.
Governance and workflow details documented in project materials emphasize reproducible annotation procedures and dataset publication, with the CVAT.AI Platform serving as the annotation engine supporting pixel wise governance, label consistency checks, and dataset export for benchmarking. The outcome recorded in the source is a public semantic segmentation dataset published in 2022 that underpins model training and evaluation for waterbody image analysis.
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Buyer Intent: Companies Evaluating CVAT.AI Platform
- Johns Hopkins University Applied Physics Laboratory, a United States based Education organization with 7600 Employees
Discover Software Buyers actively Evaluating Enterprise Applications
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