Data Labeling Services

Image Annotation

I specialize in detailed and accurate image annotation to support AI and machine learning models. My experience includes not only labeling but also performing QA to verify annotation quality and maintain dataset integrity. 

Types of Image Annotation:

  • Bounding Boxes – Drawing rectangles around target objects.
  • Polygon Annotation – Outlining irregular shapes for accurate segmentation.
  • Semantic Segmentation – Pixel-level classification of every object.
  • Instance Segmentation – Labeling each object instance separately.
  • Image Classification – Assigning categories to entire images.

Audio Annotation

I provide thorough audio annotation services with careful QA review, ensuring that all labeled data is accurate and consistent. My work supports speech models, transcription systems, and audio recognition tasks.

Types of Audio Annotation:

  • Speaker Diarization – Identifying and labeling different speakers.

  • Timestamping – Marking start and end times of words or phrases.

  • Event Annotation – Labeling specific sounds or background noises.

  • Emotion Annotation – Tagging emotional tone of speech.

NLP Annotation

I offer text annotation services that enrich raw text data with structured labels, enabling machines to understand language, intent, and context.

  • Named Entity Recognition (NER) – Identifying names of people, places, brands, etc.

  • Sentiment Analysis – Labeling emotional tone (positive, negative, neutral).

  • Intent Annotation – Categorizing user intentions in queries or messages.

  • Part-of-Speech Tagging – Assigning grammatical roles to words.

  • Text Classification – Grouping documents into predefined categories.

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Quality Assurance

I provide thorough manual QA to ensure high-quality, error-free data labeling. This includes double-checking annotations, following detailed guidelines, reviewing edge cases, and performing spot checks. I also communicate closely with the team to resolve any ambiguities and ensure consistency across all labeled data.

QA steps I follow:

  • Review and follow project guidelines

  • Double-check all annotations

  • Communicate unclear cases with the team

  • Perform spot checks on labeled data

  • Apply final quality control before submission

Frequently Asked Questions

✅ What services do you provide?

With over 12 years of experience, I provide high-quality annotation services for image, audio, and text data. My work is defined by precision, attention to detail, and a strong focus on quality assurance. I’ve led QA on every project I’ve handled, ensuring consistently clean and accurate datasets that are ready for machine learning and AI development.

  • Computer Vision Annotation
  • NLP Annotation
  • Audio Annotation
  • QA & Model Validation

I’m experienced with the most popular industry-standard annotation tools, including:

  • Labelbox

  • SuperAnnotate

  • CVAT

  • VGG Image Annotator (VIA)

  • LabelImg

  • Audacity (for audio labeling)

  • Prodigy / Doccano (for text NLP)

In addition, I quickly adapt to proprietary or internal tools and am comfortable learning new platforms as needed to meet project-specific workflows.

Throughout my career, I’ve collaborated with a wide range of companies — from startups to established enterprises — across industries including:

  • Agritech (agricultural innovation and automation)

  • Street and Traffic Security (object detection, license plate recognition)

  • Smart Cities & Public Services (city cleanliness and waste monitoring)

  • Retail AI (supermarket inventory, shelf monitoring, customer behavior)

  • Nonprofits (translation and localization of educational materials)

  • Geology & Earth Sciences (labeling geological formations and terrain analysis)

What sets my services apart is the combination of deep expertise, consistent quality, and a personalized approach. I don’t just complete tasks — I ensure every dataset is clean, precise, and optimized for its end use. With over a decade of experience and a strong QA background, I proactively catch and fix issues before they become problems. Clients value my reliability, attention to detail, and ability to adapt quickly to different project needs and tools. I’m not just a labeler — I’m a quality partner in your machine learning pipeline.

High-quality labeled data is the backbone of successful AI models. It ensures that AI systems perform accurately, make better predictions, and deliver reliable results. To maintain this standard, I follow a meticulous process that includes carefully reading and understanding the guidelines, being thorough and precise with each annotation, and double-checking all labels. I communicate closely with project managers and team members whenever something is unclear or if I have questions, ensuring alignment and clarity. At the end of each task, I also perform a final quality assurance check to make sure everything meets the required standards. Poor labeling can lead to errors, wasted resources, and a loss of trust in AI systems—which is why I’m fully committed to precision, consistency, and delivering the highest quality work.

Let’s create accurate, high-quality data together.

Available for freelance projects, ongoing support, and custom labeling needs.

Work With Me