What Is Data Annotation?
Data annotation is the process of labeling or annotating data to make it identifiable and usable by machine learning models. Data annotation quality and accuracy directly impact AI models’ reliability. In layman’s terms, data annotation refers to adding relevant and specific information to data sets, which is then fed to the machine learning (ML) algorithms so that they can understand and process them, improving their performance, accuracy, and efficiency.
For instance, a business can save manual labor costs and increase inventory management efficiency by using image recognition technology to automatically identify objects in photographs.
Focus on building amazing AI: Leave the data labeling to us
Our end-to-end data labeling services proficiently manage every project detail, from custom workflow set-up and annotator selection, to precise annotation execution and seamless final delivery, all held to the highest quality standards.
Leverage proven labeling expertise
With over 3 years of experience delivering more than two million labels annually, we are your ideal partners for data labeling projects of all scales and any complexity.
Specialized global annotation workforce
Diverse in demographics, skills and expertise, our AI Community includes labelers, linguists and subject-matter experts across different domains, vital for capturing representative data.
AI-assisted labeling and quality control
Ground Truth Studio provides sophisticated multimodal data annotation and features automated labeling, seamless project management and configurable workflows.
Multimodal data annotation
We provide diverse, accurate datasets at scale, across all data types.
3D Sensor Fusion Annotation
Elevate your 3D computer vision models to new heights of accuracy with our multi-sensor annotation services that encompass object classification, 3D object tracking, 2D-3D linking, bird's-eye-view and point cloud segmentation.
Image/Video Annotation
Extract rich information from visual content, including precise object detection, detailed segmentation, landmark recognition and accurate movement prediction across various domains and applications.
Audio Annotation
Craft a digital map of your audio with our AI-powered services. We empower your models to understand spoken language through features like speech recognition, speaker identification, detailed transcription, sentiment recognition, diarization and audio segmentation.
Text Annotation
Our text labeling services handle a vast range of scripts and languages, ensuring seamless integration for natural language processing, document processing, chatbots, transcripts and more. We offer a suite of powerful features, including classification, named entity recognition, keyphrase extraction, intent classification, question answering, sentiment analysis and text summarization.
Customize workflows to improve data labeling accuracy and throughput
Gain increased label quality with customizable workflows to orchestrate reviews throughout labeling pipelines. Effectively label the most complex scenarios with granular detail using nested ontologies and evaluate annotator performance with real-time analytics.
Model
Use AI models for accelerated labeling process
Integrate SOTA AI models such as LLaMa 3.2, GPT-4o, Gemini 1.5 Flash, and your own machine learning models to automate data labeling pipelines.
workflows
Configure workflows for quality control
Ensure quality control throughout labeling pipelines with customizable data workflows and multi-stage reviews. Assign roles, labeling tasks, and manage project completion.
analytics
Explore dynamic performance analytics
Gain at-a-glance insights with built in analytics on label quality and annotator performance, and model performance, to optimize optimize for speed and accuracy.
