Autonomous Driving DataOps
Best for multi-sensor perception production, QA, version tracking, and customer delivery in teams that already manage complex driving-data workflows.
Compare plans by project stage, individual throughput, team review needs, version gates, delivery requirements, and procurement support.
Whether you work on autonomous-driving perception data or embodied-AI task data, the first question is not feature count, but whether the workflow, quality, version, and delivery layer is complete enough for the team.
Best for multi-sensor perception production, QA, version tracking, and customer delivery in teams that already manage complex driving-data workflows.
Build data production, human review, versioning, and delivery infrastructure now so it is ready before robotics developers scale up.
What usually triggers an upgrade is not annotation alone, but whether quality control, version gates, delivery summaries, and audit actually exist.
Use core 2D/3D annotation tools to validate workflow, dataset standards, and export boundaries before committing the team to the infrastructure.
Best for validating the smallest workflow, tutorials, and small pilot datasets.
For autonomous-driving or robotics data production led by one person or a small team, with AI pre-labeling, cloud training, and model export, but without shared review, version gates, or delivery governance.
For individual- or small-team production work without team governance.
For collaborative delivery teams that need team management, role controls, task routing, version gates, delivery tracking, customer handoff, and quality control.
For multi-person review, routing, version gates, and delivery governance.
Best for enterprise deployment, SSO, audit controls, dedicated support, and enterprise procurement.
For enterprise deployment, security controls, procurement support, and deeper integration.
Use Team when you want hosted review, delivery, and audit in the cloud. Use Enterprise when enterprise deployment, procurement, or integration boundaries become hard requirements.
Stay on the hosted path when you need shared review, dataset versions, release delivery, and customer handoff without adding private infrastructure.
Take the enterprise path when the buying discussion moves into security review, procurement, tenant boundaries, or external system integration.
Use the enterprise route to confirm deployment boundaries, audit expectations, and integration scope first, instead of forcing those questions into a self-serve package decision.
Use this section to confirm what Free includes, when Pro or Team becomes useful, and when Enterprise is the right purchase path.
This is not an unlimited forever plan. It is the entry point for evaluation, tutorials, and the smallest workable project path.
One of the most important pricing decisions is whether the current bottleneck is solo throughput or collaboration throughput.
Enterprise adds deployment planning, compliance review, procurement support, and contract coordination for managed rollout.
Free and Pro solve path validation and individual throughput first; Team and Enterprise solve review, version gates, delivery, audit, and procurement next.