Lodestar is a complete management suite for developing computer vision models from video data. Our unique real-time integrated tools can help create production models 4x faster than traditional AI workflows.
Schedule a demoStop waiting weeks for the labeling to finish before you can even start experimenting and training models.
Annotation and data science operations run in parallel, off a single-source-of-truth dataset.
Learn more about dataset management1
Drag and drop video or image data into a project in any of 10+ formats. Assign one or more GPUs and invite team members.
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Parallel workflows create a virtuous circle that produces high-quality ground truth. Design a dataset, validated by model training, in days or weeks instead of months.
Domain experts and labelers start right in — no data curation or coding.
Jupyter preconfigured to the live dataset —test, filter, slice, dice without managing dataset copies.
Data scientists train and test models at any time to validate dataset quality.
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Once you meet your goals, export the dataset and model and deploy to your production environment.
Your annotation and data science teams work on the live dataset together. Data scientists can validate dataset quality and model accuracy earlier in the process, saving time and money.
Dataset management
Every project integrates a Jupyter notebook. Use our pyLucy API to access and modify raw pixels, video frames, annotations, and datasets. Requires no extra set up, no packages to install, no dependencies to resolve.
Learn moreManage available GPUs across multiple projects with the flip of a switch. You can assign a project one or more GPUs for the annotation suite and assign additional GPUs to the project's Jupyter notebook.
Eliminate video-to-image conversion and frame-based preparation and curation workflows. Lodestar natively handles all common video formats.
Our pyLucy API provides Jupyter access to any frame in any video within a few hundred milliseconds. Access all your metadata (annotations, datasets, and more) and raw pixel data down to the individual pixel.
Lodestar includes tools to monitor and manage your environment, and an IDE to create apps on the built-in AI model.
Train external inference models at any time, without juggling countless copies of the dataset. Easily assign GPUs from Lodestar's project management dashboard.
You know the drill: order up 100,000 labels and wait ... and wait. Finally, you get to train your model. Maybe you have enough labels. Maybe more than you needed. Maybe you need more. It's a slow, expensive guessing game.
With Lodestar you get continuous feedback on dataset quality. Monitor the internal AI as it gains accuracy. Identify labeling issues and provide new instructions while annotation is in progress. Modify the dataset on the fly. Train an inference model at any time to validate the dataset. When you hit your goals, stop labeling. Simple as that.
