Built for Teams That Take
Data Quality Seriously
We exist because great AI starts with great data — and great data requires people who care about every label.
Turning Raw Data Into the Foundation of Reliable AI
CoreLabel was founded on a single conviction: the quality of your training data determines the ceiling of your AI's performance.
We are a specialist data labeling and governance partner built for AI teams at Series A–C startups and growth-stage companies — the teams that need domain-expert quality without enterprise minimums or crowd-worker noise. As we scale, we grow with our clients into production pipelines and enterprise-grade deployments. Our annotators, quality leads, and data engineers work as an extension of your team — understanding your domain, your schema, and your delivery requirements.
From the first dataset pilot to ongoing production pipelines, we bring the rigour, transparency, and consistency that translates into models you can trust in the real world.
What We Stand For
Four principles that guide every annotation project and every client relationship.
Precision First
We treat every label as a decision that downstream models will act on. Speed never comes at the cost of accuracy — our QA processes are non-negotiable.
Full Transparency
You see everything: annotation guidelines, inter-annotator agreement scores, batch-level quality reports, and turnaround dashboards. No black boxes.
Security & Trust
Enterprise-grade data security, NDA-backed workflows, GDPR-compliant processes, and strict access controls across all projects. HIPAA BAA certification is on our roadmap for Q1 2027.
Scalability on Demand
Whether you need 1,000 labels for a pilot or 10 million for a production pipeline, our capacity scales to match your timeline without sacrificing quality.
What Sets Us Apart
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Domain-trained annotators — We match specialist annotators to your vertical, not generalists to every task.
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Multi-layer QA — Every batch is reviewed by a second annotator and a QA lead before delivery.
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Flexible delivery formats — JSON, CSV, COCO, Pascal VOC, or any custom schema your pipeline requires.
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Iterative feedback loops — We integrate your model feedback to continuously refine annotation quality over time.
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Compliance built-in — Our workflows are architected to GDPR standards from day one. HIPAA process alignment is active; HIPAA BAA and SOC 2 Type II certification are underway, with formal completion targeted Q1 2027
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End-to-end service — Labeling, cleaning, governance, and warehousing in a single, accountable partnership.
Have a project in mind? Let's talk.
Tell us about your dataset and we'll put together a tailored labeling plan within 48 hours.