Data Annotation Solutions: Unmatched Quality, Speed, & Security
For optimum and accurate comprehension of datasets, AI models need to understand in-depth, every little object and element parts of the dataset. Shaip’s data annotation methodology stems from incredible attention to detail, where minor objects in scans, punctuations in texts, elements in backgrounds, and silences in audio are tagged for precision.
Shaip’s Standout Features
- Gold standard annotation is ensured in every dataset delivered
- Industry & domain-specific SMEs and veterans deployed to annotate and validate data
- Precision annotation services across image segmentation, object detection, bounding box, sentiment analysis, classification, & more
- Experts to help formulate the project guidelines
Shaip Data Annotation Services – We Take Pride in Data Labeling
Text Annotation
We provide cognitive text data annotation services (or text labeling services) through our patented text annotation tool that is designed to allow organizations to unlock critical information in unstructured text. We offer comprehensive text annotation services, including named entity recognition (NER) to identify key information, sentiment analysis to understand customer opinions, text classification to categorize documents, and intent recognition for chatbot development.
- Sentiment analysis
- Summarization
- Classification
- Question answering
- Named-entity recognition
Image Annotation
Also known as image labeling, we balance scale and quality so your models generated the most accurate results with our image annotation services. We cover a wide range of techniques, including bounding box annotation for object detection, semantic segmentation for pixel-level accuracy, polygon annotation for irregular shapes, and keypoint annotation for pose estimation.
- Object detection
- Image Classification
- Pose estimation
- OCR annotation
- Segmentation
- Facial Recognition
Audio Annotation
By deploying specific linguists for every language requirement, our audio annotation services ensure datasets are labeled to improve conversational AI models, it is also known as audio labeling.
- Speech Transcription
- Speech recognition
- Speaker recognition
- Sound event detection
- Language and Dialect Identification
Video Annotation
We use a frame-by-frame approach to annotate videos, ensuring that even the smallest details of objects in the footage are accurately labeled. This process is known as video labeling.
- Object tracking and localization
- Classification
- Instance segmentation and tracking
- Action detection
- Pose estimation
- Lane detection
