The Secure Training Data Platform for Aerospace and Defense
Develop high quality training data at speed to build production-ready models faster with a wide range of collaborative tools, while keeping data security paramount through our platform designed for aerospace and military use cases.
Trusted by pioneering AI teams
Leverage Encord’s advanced labeling toolkit to annotate your data in key modalities such as image, video, SAR, RGB, geospatial and thermal.
Object Detection
Keypoint Skeleton Pose
Polyline Annotation
Instance Segmentation
Frame Classifications
Polygons
We offer the industry’s most advanced labeling ontologies enabling you to create as many nested classifications to support your labeling operation and help you create a better Ground Truth.
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“Encord made it very easy to centrally keep track of annotations, including who had made them and who had reviewed them. It also had this great interpolation tool which was especially useful for the projects we were working on.”
“Much of the task shifts to quality assurance, which is much quicker than annotating, because Encord’s micro-models automatically generated 97 percent of the labels.”
Stanford researchers decreased experiment duration from an average of 21 to 4 days, while processing 3x the images and consolidating the number of platforms used from 3 to one.
Train, test, and deploy models in automated pipelines while ensuring your model is being trained on the most informative data points using Active Learning techniques.
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From expert QA to annotator management, create fully customized, automated ML pipelines to improve the efficiency and quality of your annotation workforce.
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Encord is SOC2, HIPAA, and GDPR compliant with robust security and encryption standards.
Import data from your desired storage bucket such as AWS, Azure, Google Cloud Storage & Open Telekom Cloud OSS.
Programatically access projects, datasets & labels within the platform via API.
With Encord's collaborative annotation platform you can get to production AI faster while meeting regulatory requirements. Quickly label large training datasets from all modalities, and leverage foundation models to speed up your development process.