Data Annotation
High-quality, training-ready datasets for AI and ML models.
AI systems are only as good as the data they learn from. At LabelNest, we specialize in precise text, audio, and image annotation - ensuring your models are trained on structured, accurate, and scalable datasets.
What We Offer
Text Annotation
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Named Entity Recognition (NER)
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Sentiment and intent tagging
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Part-of-speech tagging, tokenization
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Relation and dependency labeling
Audio Annotation & Transcription
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Human-grade transcription with timestamps
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Speaker diarization (who said what)
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Emotion and tone labeling
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Keyword spotting and tagging
Image & Video Annotation
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Bounding boxes, semantic segmentation
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Instance labeling & object tracking
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Keypoints & pose estimation
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Frame-level video annotation
Dataset Collection
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Multilingual text corpora
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Domain-specific datasets (finance, healthcare, legal, etc.)​
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Speech/audio collection across accents & environments
Our Process
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Guideline Design - Collaborate with you to define schema, examples, and edge cases.
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Pilot Phase - Run a small batch to calibrate quality and adjust guidelines.
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Annotation at Scale - Deploy annotators + reviewers with role-based workflows.
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Quality Control - Multi-pass QA, inter-annotator agreement, escalation handling.
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Delivery - Clean datasets in your required format with documentation.
Use Cases
Chatbots & NLP Models
Train intent, entity, and sentiment classifier.
​Speech Models
Improve transcription, diarization, and emotion detection.
Computer Vision
Object detection, self-driving, healthcare imaging.
Custom AI Solutions
Any model that relies on labeled data.
Why LabelNest for Annotation?
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Structured workflows with logical precision.
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QA-first culture - every dataset reviewed, refined, and validated.
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Scalable teams (10 to 200+ annotators).
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Secure environments, NDA-ready, encrypted data handling.
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Persistent improvement - guidelines refined as projects evolve.
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