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Enterprise Layer Intelligence
Categories/AI Orchestration & MLOps/Centaur.ai
Centaur.ai

Centaur.ai

Founded 2017

Label and evaluate complex multimodal datasets using expert annotators and AI models

You can use Centaur Labs to label, structure, and evaluate specialized datasets for machine learning models. The service brings together medical and subject matter experts with algorithms to generate high-accuracy annotations for complex text, audio, images, video, and waveform data. Instead of relying on a single reviewer, multiple experts and AI systems evaluate the same records, and an aggregation system extracts the highest-quality signal. You can receive your finalized training datasets ready for production through APIs, JSON, CSV, or DICOM files.

What Centaur.ai does

Design specialized labeling schemas for complex datasetsExport annotated data directly to DICOM or JSON formatsTest dataset cost versus accuracy tradeoffs in real timeEvaluate LLM output accuracy using domain specialistsScore and rank labeler accuracy against ground truthAggregate multiple independent labels into a unified consensusCompetitive annotation system pitting human experts and AI models against each otherSignal aggregation combining top-performing human and automated labelsSupport for multimodal data including text, audio, video, waveform, and imagesNetwork of over 100,000 qualified subject matter expertsInteractive quality playground to model labeling cost against expected accuracyCustom dataset exports via API, JSON, CSV, and medical-grade DICOM formatsPerformance-based compensation and scoring for annotators

Tutorials & Demos

Frequently asked

Amazon S3, REST API, Python SDK, Cloud Storage Buckets, Custom Webhooks

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Centaur Labs, data annotation, medical labeling, dataset design, multimodal labeling, image annotation, audio labeling, waveform labeling, DICOM labeling, machine learning data, expert labelers, model evaluation, skin lesion classification, retinal OCT grading, ICD-10 mapping