Define and label the objects that matter to your robot’s task, with consistent categories across complex scenes.
Use detailed segmentation and polygon annotations to distinguish objects, surfaces and backgrounds in visual training data.
Bring context to scenes where lighting, clutter and partial visibility make objects harder to identify.
Work with specialists who understand technical structures and physical defects, helping resolve annotations that require more than visual recognition.
Review ambiguous examples with your team and refine guidelines as unfamiliar objects and situations emerge.
Align annotators on your task definitions, review their work and resolve discrepancies before they carry through into model training.
Robotics data needs more than labels. We bring specialist knowledge, careful review and flexible workflows to help your team build datasets with the context your models need.
From complex visual scenes to engineering details, we connect your project with people who understand what they’re labeling.
Clear guidelines, task-specific training and regular reviews keep your annotations aligned with your requirements.
Scale your data workflow as your robotics project grows, with a team that adapts to changing volumes and priorities.
We help prepare and review the data behind your models, from object detection and segmentation to dataset curation and human evaluation. Share your use case and we’ll work with you to define the right workflow.
Yes. We match the team to your data, task and domain requirements. For work that needs specialist judgment, we bring relevant domain expertise into the annotation process.
Timing depends on your data, annotation requirements and the expertise needed. Share a sample and your target timeline so we can scope the work and agree on a setup plan.
We establish clear guidelines, train annotators for your task and review their work throughout the project. Calibration and feedback help resolve ambiguous cases and keep labels consistent as the dataset grows.
Yes. We can support recurring data work as your requirements evolve, adjusting the team, guidelines and review process to reflect new tasks and environments.
Our computer vision capabilities include bounding boxes, polygon annotations, semantic segmentation and image classification. We also support data curation and annotation validation. Tell us about your data and intended use so we can confirm the right approach.
Yes. SUPA’s annotation platform lets teams view tasks, review quality and manage workflows. We’ll work with you to establish how it fits into your robotics data pipeline.
Our selection process includes assessments and interviews, followed by training for the specific task. We align the team on your labeling requirements before scaling the work.
Pricing depends on the data, annotation complexity, specialist expertise, volume and review requirements. Share your brief and a representative sample for a tailored quote.
Tell us what you’re building, what your model needs to learn and the data you already have. A sample dataset, draft labeling guidelines, expected volume and target timeline help us scope the next steps.