Managed labeling, SLA-backed.
A large in-house team of LiDAR and multi-sensor specialists, delivering production-grade labels for safety-critical systems. Trained, managed, and QA'd directly by Deepen, never crowdsourced, and run on the same Annotate platform your output ships on.
Managed team, or the tool your team runs.
Annotation is where most data programs slow down or break. Our managed service is built for execution; the Annotate product puts the same tools in your hands.
Annotate as a Service
One in-house team, owned end to end, scaling with your program. Backed by an SLA on accuracy and turnaround, and run on the same platform your output ships on.
Talk to our annotation team →Annotate
The multi-sensor labeling platform your team operates directly. AI-assisted, human-verified, and exporting to ASAM OpenLABEL and every format your training loop expects.
See the Annotate product →Built for execution.
A substantial workforce we hire, train, manage and QA directly. Never crowdsourced.
A dedicated project manager owns accuracy, turnaround and communication.
Capacity flexes with your roadmap: surging for a push, easing off between milestones.
Fluent in 3D point clouds, sensor fusion, and the conventions safety-critical perception demands.
Backed by engineering and our own platform, so edge cases and format changes get solved, not stalled.
Accuracy and turnaround held to an SLA, measured every batch and reported back.
Every annotation type your stack needs.
One team across 2D, 3D, and fused sensors, labeling on the same tools that run the Annotate product.
Bounding boxes, polygons, semantic and instance segmentation, keypoints, and object tracking with temporal consistency across frames.
3D bounding boxes, point-cloud semantic and instance segmentation, polylines, and multi-frame tracking.
Label once across calibrated camera, LiDAR, and radar. Annotations stay aligned in 3D and project cleanly into every sensor view.
Scenario tagging, behavior and intent labeling, and event annotation that give planning and prediction models context.
A dedicated team, reporting you can act on.
The same engagement model backs every Deepen service, framed here for annotation programs.
Sensors, label types, taxonomy, accuracy targets, and turnaround, mapped to your program.
A dedicated program manager owns accuracy, turnaround, and communication throughout.
A focused pilot labels a sample set and confirms accuracy and taxonomy fit first.
The team flexes to match your roadmap, with full QA and reporting on every batch.
Every label, checked to 99.5%.
Quality is engineered into the workflow, not inspected in at the end. Layered review takes labels from a strong first pass to full-QA accuracy on the same platform your output ships on.
Reviewers sample across every batch with inter-annotator agreement scoring, so issues are caught early, not after delivery.
In-tool comments route corrections straight back to the labeler, closing the loop in the workflow rather than over email.
Platform validations flag geometry, taxonomy, and consistency errors, gating each dataset to 99.5% full-QA accuracy before it ships.
Labels safety-critical programs build on.
Put our annotation team on your data.
Tell us about your program, label types, and timeline. We'll deliver human-verified labels against an SLA you can plan around.