Looking for reliable Natural Language Annotation Services across the UK, US, Europe and Africa? Aya Data partners with you to deliver precise annotations, accelerating AI and machine learning success. Achieve your AI goals with us!
What is Natural Language Annotation?
Natural language annotation is the process of adding labels, tags, or metadata to text data to identify linguistic features, meaning, or structure. Aya Data harnesses natural language annotation to help AI systems understand and process text data effectively, enabling businesses to extract valuable insights, automate summaries, and make better decisions from their digital text.
Organisations that trust us
Natural Language Annotation Services
Aya Data’s expert linguists provide high-quality natural language annotations to help you build accurate training datasets for your NLP projects.

Named Entity Recognition Annotation
We customize NER solutions to extract and categorize specific information like names, organizations, and locations from your unstructured text data across various sources.
Supervised Named Entity Recognition
Supervised NER trains models using labeled data to automatically identify and classify entities in new text. Our labeled datasets help build accurate NER models for your specific needs.
Open Named Entity Recognition
We customize NER solutions to extract and categorize specific information like names, organizations, and locations from your unstructured text data across various sources.
Targeted Named Entity Recognition
Our experts develop custom NER systems that target specific entities in your text, combining NLP and machine learning techniques to deliver precisely tailored entity recognition solutions.

Sentiment Analysis Annotation
We label text and audio data to identify sentiment direction and intensity, enabling machine learning models to accurately analyze customer feelings.
Expressive-Subjective Tagging
We analyze and tag customer feedback to identify emotional tone and sentiment, helping develop accurate models that understand the nuances of customer opinions.
Rule-Based Sentiment Analysis
Words and phrases are classified by their emotional polarity using predefined rules to quickly determine whether text expresses positive, negative, or neutral sentiment.
Objective-Speech-Event Tagging
This method classifies audio and speech by identifying specific events like compliments or criticism, enabling AI algorithms to analyze sentiment in spoken communications.

Audio and Sound Annotation
We combine AI tools and manual tagging to classify audio elements like speech, music, and sounds, helping users efficiently search and locate specific audio content.
Speech-to-Text Transcription
We enhance speech-to-text accuracy by annotating key audio elements including speaker characteristics, accents, and background conditions to improve transcription quality.
Audio Classification and Labeling
Our experts combine manual expertise with AI tools to accurately classify audio content by genre, artist, and emotion, delivering efficient and precise audio data annotation.
Event Classification
We segment and annotate audio recordings to identify specific events, enabling quick analysis and monitoring of sound patterns for security and communication purposes.

Text Annotation
Our experts provide customised text annotation services, identifying linguistic elements and entities to help build effective machine learning models aligned with your specific requirements.
Text Categorisation
We enable both automated and manual text categorization to help ML models identify topics across large document sets, enhancing search and document management capabilities.
Semantic Annotation
We enhance ML models’ language understanding through semantic tagging, helping them accurately interpret context, dialects, and meaning for more precise predictions.
Entity Linking
We connect textual entities to knowledge base references, enriching NLP models’ contextual understanding to improve text classification and sentiment analysis accuracy.
Industries We Serve
We provide high-quality data annotation services across a range of industries and use cases.
Agriculture
Healthcare
Robotics

Use Cases
Learn how AI enhances natural language processing by powering real-time translation, customer service automation, fraud detection and more to drive efficiency and insights across industries.


Healthcare Diagnostics Support
Analyze patient records, symptoms, and research to assist clinicians in faster, data-driven diagnoses.
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Multilingual Translation Services
Offer real-time, context-aware translation for global communication in business or customer support.
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Customer Service Automation
NLP powers chatbots to resolve queries instantly, reduce wait times, and analyze feedback for service improvements.
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Fraud Detection in Finance
Monitor transactional text data (emails, claims) to identify suspicious patterns and prevent fraud.
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HR Recruitment Optimisation
Automate resume screening, candidate matching, and interview analysis to accelerate hiring processes.
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E-Commerce
Enhance shopping experiences with NLP-driven product recommendations based on user behavior and search history.
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Legal Document Analysis
Extract key information, classify documents, and ensure compliance through automated text annotation.
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Sentiment Analysis for Brands
Track social media, reviews, and surveys to gauge public sentiment and refine marketing strategies.
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Selected Case Studies
We help businesses of all sizes effectively navigate their AI journey.
Vehicle Damage Detection Speeds Claims
Secure 3D Medical Data Annotation Solutions
Infrastructure Damage Detection Made Precise
Satellite Analysis for Environmental Protection
E-Scooter Detection for Autonomous Vehicles
Advanced Retail Security Through AI
Police Radio Transcription At Scale
Expert Medical Image Data Labeling
What Our Clients Say About Us









The Aya Advantage
1/ Exceptional Customer ExperienceExceptional Customer Experience
Unwavering Quality
Unparalleled Subject Matter Expertise
Featured News and Insights
Enjoy featured articles and insights from our experts.
How to Find Training Data for Machine Learning
The Art of the Dataset
Crowdsourcing Vs. Managed Service Vs. In-House Labeling
Manual Vs. Automated Data Labeling
Is Synthetic Training Data the Future of Machine Learning?
Frequently Asked Questions
What are natural language processing services?
What are the common NLP techniques?
What is sentiment analysis in NLP?
Why is NLP important for businesses?
How does NLP work in chatbots?
Can NLP be used for voice assistants?
What industries use NLP services?


Simplify Your AI Development Today!
Do you need help with Data Acquisition, Data Annotation or building a custom AI model? Aya Data is ready to partner with you. Talk to us today!