Everyone labels pictures.
We label decisions.
Expert annotation for the hardest training data there is — agentic AI workflows, robotics episodes, and the specialized datasets underneath them. Every batch held to a published quality floor.
Two Frontiers Where Training Data Is Hardest
Generic annotation is a solved problem. Sequential decision data — agents acting over many steps, robots acting in the physical world — is not. These are the two areas we build for first.
Agentic AI Workflow Annotation
Multi-step agent trajectories — every tool call, every branch, every recovery from a wrong turn — labeled against a ground-truth schema.
- Environment & sandbox harnesses that generate real episodes
- Trace ingestion from LangChain, AutoGPT, CrewAI or custom frameworks
- Tool-choice & parameter correctness scoring
- Multi-agent handoff & delegation quality
- Long-horizon memory and path-efficiency labeling
Robotics Annotation
Physical-world episodes across synchronised sensor streams — pose, grasp, kinematics, and the safety events that matter most.
- Multi-sensor ingest — ROS bags, LiDAR, depth, IMU, force-torque
- 3D scene, object pose & grasp-point annotation
- Joint-angle and end-effector trajectory labeling
- Human demonstration capture for imitation learning
- Collision & human-robot interaction safety labeling
One trajectory model. Built once, used twice.
A digital agent choosing a tool and a robot arm choosing a grasp are the same shape of problem: state, action, outcome, repeated over time. We model both on one schema, review both in one timeline viewer, and export both through one pipeline — so quality standards, tooling, and your team's mental model carry across from digital to physical.
Moving Beyond Generic Tagging
Precision-crafted data services built for the demands of modern AI — from foundation models to autonomous agents.
Specialized Expert Networks
Medical, legal, and scientific annotation by credentialed domain experts — not generalist crowdworkers.
Adversarial & Bias Auditing
Red-teaming datasets and bias detection pipelines that make your models safer before they ship.
Compliance & Governance
Workflows architected to GDPR standards from day one, with full audit trails and data residency controls. SOC 2 Type II certification is underway; HIPAA BAA and EU AI Act compliance are on our roadmap for Q1 2027.
How We Work
From raw data to model-ready output in three transparent steps.
Submit Your Data
Share your raw dataset — text, images, video, audio, or time series — via our secure upload portal, or API access, or your secured data store.
Expert Labeling & QA
Our trained annotators label your data with multi-layer quality assurance, including inter-annotator agreement checks and senior review.
Receive Clean Output
Get your labeled dataset delivered in your preferred format — JSON, CSV, COCO, YOLO, or custom schema — ready to plug into your training pipeline.
The Quality Lifecycle
Six precision stages — from raw data intake to export-ready ground truth. Click any node to explore what CoreLabel does at each step.
Built from Day One
CoreLabel is designed for compliance from the ground up. Our workflows are architected to GDPR and HIPAA standards, with SOC 2 Type II certification underway. Annotator-level NDAs, VPC deployment options, and timestamped audit trails are available today. HIPAA BAA and formal certifications are on our roadmap for Q1 2027.
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GDPR Compliant workflows & data handling
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HIPAA Architecture & process alignment
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SOC 2 Type II Audit currently in progress
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HIPAA BAA Formal business associate agreement
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ISO 27001 Information security certification
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CCPA Privacy law formal compliance
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ISO 10218 & ISO/TS 15066 Robot safety & collaborative-operation standards, mapped for our robotics annotation pillar
Ready to build AI you can trust?
Start your first labeling project today — precise annotations, proven QA, and a team that treats your data like their own.