You will get High-Quality Image & Video Annotation for AI Training Datasets
Project details
I specialize in high-quality AI training data services including image annotation, video labeling, data collection, and QA review. What sets my work apart is my strong attention to detail, strict adherence to annotation guidelines, and focus on maintaining data integrity across large-scale datasets.
I ensure every dataset is consistent, accurate, and production-ready for computer vision and machine learning models. I am also highly adaptable to different tools and workflows, making collaboration with AI teams smooth and efficient.
I ensure every dataset is consistent, accurate, and production-ready for computer vision and machine learning models. I am also highly adaptable to different tools and workflows, making collaboration with AI teams smooth and efficient.
What's included
| Service Tiers |
Starter
$10
|
Standard
$50
|
Advanced
$100
|
|---|---|---|---|
| Delivery Time | 1 day | 2 days | 3 days |
Number of Revisions | 1 | 2 | 3 |
Number of Model Variations | 1 | 1 | 1 |
Number of Scenarios | 0 | 1 | 2 |
Number of Graphs/Charts | 0 | 0 | 0 |
Model Validation/Testing | - | - | - |
Model Documentation | - | - | - |
Data Source Connectivity | - | - | - |
Source Code | - | - | - |
Optional add-ons
You can add these on the next page.
Priority Delivery (24 hrs).
+$15
Express Delivery (12 hrs).
+$20
Extra Revisions.
(+ 1 Day)
+$10Frequently asked questions
3 reviews
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Very urgent Image Labeling and Annotation Review for 6000 Images
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About Nehemiah
Data Annotation Specialist | QA & Data Evaluation
100%
Job Success
Nairobi, Kenya - 3:42 am local time
My work covers the full data pipeline, including data collection, annotation, quality assurance, and dataset validation to ensure accurate, consistent, and production-ready datasets across complex AI systems.
I work with image, video, audio, and text data, supporting end-to-end dataset preparation through labeling, review, and QA to deliver reliable training data for machine learning and computer vision models.
💼 CORE SERVICES
✓ Data collection (image, video, audio, text)
✓ Image annotation (bounding boxes, polygons, keypoints, cuboids)
✓ Video annotation and object tracking
✓ Semantic segmentation for computer vision datasets
✓ Data labeling and classification
✓ AI training data preparation and structuring
✓ Dataset cleaning, review, and validation
✓ Annotation quality assurance (QA checks and corrections)
✓ Data consistency checks and error detection
✓ Text annotation (NLP labeling, entity tagging, sentiment analysis)
✓ Audio annotation (transcription, segmentation, labeling)
📦 DELIVERABLES
✓ Clean, structured, production-ready AI training datasets
✓ Fully labeled datasets following strict project guidelines
✓ High-accuracy annotations for machine learning models
✓ Validated datasets with quality assurance checks
✓ Consistent, error-free labeling across large datasets
✓ Well-structured datasets ready for AI model training
✓ Data collection outputs organized for AI pipelines
✓ QA-reviewed datasets with corrections and improvements
✓ Fast, reliable delivery of large-scale annotation projects
✓ Dataset formats compatible with client tools and workflows
⚙️ TOOLS & PLATFORMS
✓ CVAT
✓ Labelbox
✓ Roboflow
✓ Label Studio
✓ Supervisely
✓ SuperAnnotate
✓ Segments.ai
✓ Hasty.ai
✓ Single Review Tool (SRT)
🌍 AVAILABILITY
Available for both short-term and long-term projects.
I adapt quickly to client tools, workflows, and data requirements, ensuring smooth integration into any AI data pipeline.
📩 CALL TO ACTION
If you need high-quality data collection, annotation, and validated AI training datasets, feel free to invite me to your project or send a message. I am ready to start immediately and deliver reliable, production-ready results.
Steps for completing your project
After purchasing the project, send requirements so Nehemiah can start the project.
Delivery time starts when Nehemiah receives requirements from you.
Nehemiah works on your project following the steps below.
Revisions may occur after the delivery date.
Review Project Requirements
I carefully review the annotation guidelines, dataset files, class definitions, and output format. This ensures full understanding of the task before starting any labeling work.
Sample Annotation (If Required)
I create a small sample batch of annotations based on the guidelines for client review. This helps confirm alignment before scaling to the full dataset.