Precision labeling at scale
Data Annotation
High-precision multi-modal labeling for computer vision, NLP, and multimodal AI systems with multi-layer QA.
Overview
What is Data Annotation?
Data annotation is the process of labeling raw data — images, text, audio, video — so machine learning models can understand and learn from it. Without high-quality annotated data, even the most advanced AI models fail to perform accurately.
Why it matters: Foundation models are trained on billions of annotated examples. The quality, consistency, and diversity of that labeled data directly determines model performance, safety, and real-world reliability.
Image & Video
Bounding boxes, polygons, keypoints, semantic/instance segmentation
Text & NLP
NER, relation extraction, sentiment, intent, coreference
Audio
Speaker diarization, speech alignment, sound event tagging
Quality Control
95%+ accuracy guarantee with IAA scoring and multi-pass QA
Workflow
How We Do It
01
Project Scoping
We assess dataset requirements, define annotation taxonomy, and assign domain-specialized annotators matched to your AI use case.
02
Style Guide Creation
Comprehensive annotation guidelines and calibration batches ensure consistency before full-scale annotation begins.
03
Precision Labeling
Expert annotators label bounding boxes, polygons, keypoints, semantic segments, named entities, and relationships.
04
Multi-Layer QA
Automated consistency checks, inter-annotator agreement scoring, and senior expert review on every batch.
05
Structured Delivery
Export-ready datasets in COCO, YOLO, Pascal VOC, JSON formats with full audit documentation.
Case Study
E-commerce Platform
E-commerce Platform
Annotate 300K product images for visual search engine
Solution
Multi-label classification plus bounding box pipeline for product attributes
Results
300K
Images annotated
97%
Precision score
6 wks
Delivery
Ready to Get Started with Data Annotation?
Tell us about your project and we'll scope a pilot within 48 hours.