Ethical, Expert, Human-Powered AI Data Annotation

Annotation workflows built on measurable excellence

Every AI dataset is validated against strict benchmarks for accuracy, consistency and reliability:

• Accuracy First: We consistently achieve precision and recall rates above 90%.
• Consistency Matters: Multi-pass reviews ensure expert agreement for subjective and complex tasks.
• Specialized Metrics: From IoU for image annotation to WER for transcription, we apply advanced industry-trusted measures to guarantee top-tier quality.

Expert Annotation for Any Data Type

We deliver annotation for image, audio, text, video, and multimodal—ensuring accuracy and scalability for your AI training needs.

Audio

Transform raw audio into structured, labeled datasets for speech and language models:

• Automatic Speech Recognition (ASR): Annotate transcripts for accurate speech-to-text conversion.
• Human Transcription: High-quality manual transcription for nuanced language understanding.
• Speaker Diarization: Identify and separate speakers in multi-party conversations.
• Natural Language Annotation: Tag linguistic features like intent, sentiment, and tone.

Image

Enable computer vision systems with precise image labeling:

• Bounding Boxes: Detect and localize objects within images.
• Polygon Annotation: Outline complex shapes for detailed segmentation.
• Image Classification: Categorize images into predefined classes.
• Facial Recognition: Annotate facial landmarks for identity and emotion detection.
• Semantic Segmentation: Assign pixel-level labels for scene understanding.

Video

Train models for dynamic environments and motion-based tasks:

• Object Tracking: Follow objects across frames for movement analysis.
• Action Recognition: Label human or object actions for behavioral modeling.
• Event Detection: Identify key events in video streams.
• Video Classification: Categorize videos by content type or context.
• Captioning: Generate descriptive text for video content.

Text

Structure and enrich text data for Natural Language Processing (NLP) applications:

• Sentiment Analysis: Tag emotional tone for opinion mining.
• Named Entity Recognition (NER): Identify entities like names, locations, and dates.
• Content Moderation: Flag inappropriate or harmful content.
• Linguistic Annotation: Mark syntax, grammar, and semantic roles.

Multimodal

Support advanced AI that integrates multiple data types:

• Robotics: Annotate sensor and visual data for autonomous systems.
• Image-Text Pairs: Link visual content with descriptive text.
• Video-Text Annotation: Align video frames with narrative or instructions.
• Audio-Text Transcription: Combine speech and text for conversational AI.
• Cross-Modal Linking: Connect entities across different modalities for richer context.