For fast-moving ML teams, the biggest bottleneck isn't training models—it's sourcing clean, accurate, and reliable training data. We solve this. We provide quality-first visual data annotation designed to eliminate iteration loops and accelerate your path to production.
Our human-in-the-loop process guarantees precision at scale. We don’t just run your data through a model. Every label is placed, reviewed, and validated by expert annotators who understand your data’s context. To ensure the highest standards of quality and security, all annotation is performed by our specialist team in Poland and is never outsourced. This methodology, backed by a research partnership with AGH University of Science and Technology, applies scientific rigor to every dataset we deliver.
We adapt to your project at every step. Whether you need data tomorrow or next month, we scale our team to meet your timeline. Your data stays yours, protected by secure, access-controlled workflows built to meet your requirements.
Our Core Areas of Expertise:
To deliver the highest quality, we cultivate deep domain knowledge. We specialize in providing context-aware data for leaders in:
Automotive: Supporting the development of ADAS and autonomous systems with precise 2D, 3D, and LIDAR annotation.
Medtech: Annotating medical imagery with anatomical precision for diagnostic and research applications.
Industrial & Manufacturing: Labeling machinery, defects, and production flows to automate visual inspection.
Don't see your industry? Our adaptive process allows us to build custom annotation pipelines for any use case. Reach out to discuss your project's unique needs.
Our Core Services Include:
2D & 3D Bounding Boxes
Semantic & Instance Segmentation
LIDAR Point Cloud Annotation
Custom annotation pipelines tailored to unique use cases.
Start building better models! Visit our website or message us here. We will answer as fast as possible!
Data Annotation Services for AI & Machine Learning Company
Data Annotation Services
$50,000 to $199,999
Jan. - Sep. 2025
5.0
Quality
5.0
Schedule
5.0
Cost
5.0
Willing to Refer
5.0
"What impressed me most about this company was the exceptional quality of their work."
Oct 1, 2025
Director, AI & Machine Learning Company
Anonymous
Verified
Education
Krakow, Poland
11-50 Employees
Online Review
Verified
Data Sphere Lab provided data annotation services for an AI and machine learning company. The team annotated a data set of over 10,000 high-resolution dental X-ray and CBCT images.
Data Sphere Lab's work achieved an inter-annotator agreement of over 98%, boosting the client's model performance by 12%. The team had outstanding project management, consistently delivering all items promptly. They were highly responsive and adapted quickly to the client's needs.
The client submitted this review online.
BACKGROUND
Please describe your company and position.
I am the Director of an education company
Describe what your company does in a single sentence.
Advanced AI projects for industry and healthcare
OPPORTUNITY / CHALLENGE
What specific goals or objectives did you hire Data Sphere Lab to accomplish?
Data Annotation for Dental Imaging Conducted precise annotation of dental images, including intraoral X-rays, panoramic radiographs, and 3D CBCT scans. Tasks included segmentation of anatomical structures (e.g., teeth, roots, bone), detection of caries and lesions, and classification of dental conditions.
Data Annotation for Multimodal Autonomous Driving Systems Performed high-quality data annotation for autonomous vehicle systems using multimodal datasets, including LiDAR, camera (RGB), radar, and GPS inputs. Tasks included 2D and 3D object detection, semantic segmentation, lane detection, and sensor fusion alignment.
SOLUTION
How did you find Data Sphere Lab?
Online Search
Other
Why did you select Data Sphere Lab over others?
High ratings
Pricing fit our budget
Great culture fit
Good value for cost
Company values aligned
How many teammates from Data Sphere Lab were assigned to this project?
25
Describe the scope of work in detail. Please include a summary of key deliverables.
We collaborated with DataSphereLab on a computer vision project focused on medical image analysis, specifically in the dental domain. The team was responsible for comprehensive data annotation services, including segmentation of anatomical structures such as teeth, jawbones, and lesions, as well as classification tasks for detecting dental caries, missing teeth, and bone loss. The scope of work included: Annotating a dataset of over 10,000 high-resolution dental X-ray and CBCT images. Creating custom labeling protocols and annotation guidelines in alignment with clinical standards. Delivering multilabel masks in JSON and DICOM-compatible formats. Performing quality control checks with a dual-review process to ensure clinical-grade accuracy. Providing weekly progress reports and dataset statistics to maintain transparency. The final deliverables included a fully labeled dataset ready for training deep learning models, documentation of the labeling methodology, and a brief report on edge cases and annotation challenges. The work was delivered on time and met all of our quality and compliance requirements.
RESULTS & FEEDBACK
What were the measurable outcomes from the project that demonstrate progress or success?
The collaboration resulted in several tangible outcomes that clearly demonstrated project success:
Annotation Accuracy: Achieved over 98% inter-annotator agreement, validated by clinical experts, ensuring the dataset was suitable for training diagnostic-grade AI models.
Model Performance Boost: Using the annotated dataset, our initial AI prototype improved in precision and recall by +12% compared to models trained on publicly available data.
Delivery Speed: The team annotated over 10,000 images within eight weeks, ahead of schedule, enabling us to accelerate our development timeline.
Compliance: All deliverables were prepared in accordance with HIPAA-compliant data handling protocols and aligned with our internal documentation standards.
Documentation Quality: The clear and well-structured annotation guidelines and handoff documentation streamlined internal onboarding for new ML engineers.
These results significantly advanced the AI development phase and proved critical in moving toward regulatory readiness for our medical imaging platform.
Describe their project management. Did they deliver items on time? How did they respond to your needs?
The team demonstrated excellent project management, consistently delivering all items on time. They were highly responsive, adapted quickly to our needs, and maintained clear communication throughout the project.
What was your primary form of communication with Data Sphere Lab?
Virtual Meeting
Email or Messaging App
What did you find most impressive or unique about this company?
What impressed me most about this company was the exceptional quality of their work and their deep expertise in AI and data annotation. Their ability to handle complex tasks with precision, combined with a proactive and collaborative approach, truly set them apart.
Are there any areas for improvement or something Data Sphere Lab could have done differently?
No, there are no areas for improvement — the collaboration was smooth, and all expectations were fully met.
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