Data Annotation Services

AI Data Labeling for Computer Vision, NLP, and Audio

Accurate, scalable ground truth for machine learning teams. Human-validated annotation with AI-assisted workflows built for production-grade model training.

Managed WorkforceHuman-in-the-Loop QASecure Data HandlingMultilingual (EN / 中文)

Annotation Services Across Every Modality

End-to-end data labeling for computer vision, natural language, audio, and document AI workflows.

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Image & Video Annotation

Bounding boxes, polygons, semantic segmentation, keypoint annotation, and object tracking. We also support data collection and sourcing for vision datasets.

PERSONLOCATIONDATEORGANIZATIONMONEYPOSITIVE 0.87SENTIMENT

Text & NLP Labeling

Named entity recognition, intent classification, sentiment analysis, and text categorization for language models.

Speaker ASpeaker BSpeaker A00:0000:1200:2400:34"The quarterly results show a 12%..."

Audio Annotation

Transcription, speaker diarization, timestamping, and phonetic labeling for speech and audio AI systems.

EXTRACTED FIELDSvendor:Acme Corpdate:2026-03-15total:$4,280.00confidence: 0.96

Document AI

OCR correction, form field extraction, table parsing, and document classification for structured data pipelines.

AI MODELpre-labelHUMAN QAvalidatedthroughput+60%accuracy99.2%human-verified100%

AI-Assisted Pre-Labeling

Machine learning pre-annotation accelerates throughput. Every output is reviewed and validated by trained human annotators.

CONSENSUSGOLD TESTREFEXPERTQUALITY REPORTprecision0.984recall0.971IAA0.938

QA & Review Workflows

Multi-stage validation with consensus scoring, gold standard testing, and expert audit for production-grade accuracy.

From Pilot to Production

01

Scoping

We define annotation guidelines, acceptance criteria, and project architecture based on your model requirements.

02

Pilot

A sample batch validates our approach — typically delivered within 5–7 business days. We calibrate quality, refine guidelines, and align on delivery format.

03

Production

Managed annotators work with AI-assisted pre-labeling. Multi-stage QA ensures every label meets your accuracy threshold.

04

Delivery

Labeled datasets delivered in your preferred format with full audit trail and quality documentation. Production SLAs defined per project.

A Managed, Professional Annotation Workforce

Every project is staffed by vetted, trained annotators who work under professional agreements. We scale teams from 5 to 50+ annotators per project, with native-level support in English and Chinese (Mandarin).

Vetted & Trained

Annotators are screened, onboarded, and tested on project-specific guidelines before production begins.

Domain Specialists

We staff projects with annotators who have relevant background — medical imaging, autonomous driving, financial documents, content moderation.

Accountable & Secure

All team members operate under NDAs and data handling agreements. Work is tracked, auditable, and tied to named individuals.

Multilingual Operations

Native English and Chinese (Mandarin) annotation teams. We support bilingual labeling, cross-lingual QA, and CJK-specific text processing.

Three-Stage Validation for Every Project

01

Consensus Annotation

Each task is independently labeled by multiple annotators. Agreement scoring ensures only high-confidence labels advance.

02

Gold Standard Testing

Annotators are continuously evaluated against pre-verified reference data. Performance below threshold triggers retraining or removal.

03

Expert Review

Senior reviewers audit output samples. Clients receive quality reports with precision, recall, and inter-annotator agreement metrics.

Domain Expertise Where It Matters

Healthcare & Life Sciences

Medical image annotation, clinical document labeling, and de-identified dataset preparation for health AI applications.

Automotive & Robotics

LiDAR point cloud annotation, 3D bounding boxes, lane marking, and object tracking for autonomous systems.

Financial Services

Document extraction, fraud detection labeling, and transaction classification for compliance-aware AI models.

Trust & Safety

Content moderation labeling, policy violation detection, and sentiment classification for platform integrity teams.

Your Data, Protected

We design every workflow around data security and client requirements.

Encryption

All data encrypted in transit (TLS 1.2+) and at rest (AES-256).

Access Control

Role-based permissions with least-privilege enforcement across all environments.

Client-Owned Tools

We work inside your annotation platform — CVAT, Labelbox, Label Studio, Supervisely, or custom tooling — so data never leaves your environment.

PII Handling

De-identification, masking, and redaction workflows for sensitive datasets.

Audit Trails

Every annotation action is logged. Full provenance documentation on every delivered dataset.

Privacy-Conscious

Workflows designed to support GDPR, CCPA, and HIPAA-adjacent requirements. We adapt to your compliance framework.

Ready to Start a Pilot Project?

Tell us about your annotation requirements. We will scope a pilot, deliver a sample batch, and show you what production-quality labeling looks like.

Request a Pilot