Data Annotation Services
On Demand, Scalable Data Annotation Services
Obtain high-accuracy structured data for your AI and Machine Learning models. Get consistent, high-quality data at a massive scale.
BUNCH allocates teams of in-house, highly skilled annotators trained to handle all types of data—text, images, audio, and videos. We secure the highest quality annotation results through double-pass annotation techniques and strict QA processes.
Meet your short and long-term volume needs for data labeling at scale. BUNCH allocates annotation teams trained to secure the highest work output quality through strict QA and double-pass annotation techniques.
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Unmatched Accuracy Standards for AI and ML
We understand that even a few errors in your training data can compromise the integrity of entire datasets. Over the past years, we have diligently refined our QA audit processes, trained our labelers, and determined the ideal team structure balance among Labelers, Team Leads, Quality Assurance Specialists, and Project Managers to deliver the highest possible data quality without sacrificing productivity.
We continuously enhance our QA Scorecards and retrain our annotators and linguists based on guidelines through iterative improvements, adding what we learned from client-specific edge cases in each iteration. We carefully select the most suitable labelers for each training data media type. BUNCH counts with a seasoned team of high-touch project managers who have had extensive exposure to ML models, and our entire organization is guided by a single, shared mantra: Data Quality.
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We handle Data Ops Projects from Thousands fo Billions of Datapoints
We assign compact teams consisting of a few annotators to handle smaller projects involving several thousand images or audio files and deploy teams of dozens of annotators for large-scale projects spanning several months. To ensure rapid response and scalability, we maintain a large pool of experienced annotators who can be mobilized within days, reaching hundreds of labelers when necessary. Projects can be structured based on an agreed output, such as millions of labeled images or hundreds of hours of transcribed speech audio in various languages.
For many clients in the AI space, we arrange full-time teams with a specified number of FTEs (Full-Time Employees) to address recurring data needs, which is the most cost-efficient approach for generating substantial volumes of training data for long-term ML models requiring ongoing data input. Occasionally, we maintain a fixed team to produce a specific amount of data while employing a flexible, part-time team to manage seasonal surges.
Pricing is determined based on output, such as the number of images labeled, audio hours transcribed, polygons or bounding boxes annotated, and text clips categorized. Alternatively, it can be based on the number of Full-Time Employees (FTEs) allocated to the project.
Train your ML Models with Proven and Tested Labeling Techniques and Industry Experts
Our Data Ops Team boasts industry experience in providing training data for AI and ML applications, with a particular focus on computer vision. This includes data tagging for various domains such as self-driving vehicles, healthcare, robotics, precision agriculture, geospatial intelligence, education, energy, and medical AI. We collaborate with numerous R&D departments at top universities in the US, UK, Singapore, Canada, and China. We support Natural Language Processing AI programs for global organizations across various industries, including retail, eCommerce, manufacturing, and private Deep Learning initiatives.
Our processes and technology have enabled our clients to maintain a consistent flow of structured training data that powers algorithms by utilizing human inputs and intelligence. We allocate teams to operate 24/7 when a project's quick turnaround time is vital.
Before onboarding our clients, we typically perform a calibration test, in which we run a labeling trial using a representative data sample from the entire dataset. This helps us understand the guidelines (and suggest improvements for increased efficiency), determine the average handle time (AHT) for each task, and design the most optimized team for scaling the task effectively.
DATA ANNOTATION
TECHNIQUES WE MASTER
Image Annotation
Categorize and label objects within images
Semantic Image Segmentation
Annotation of segments in images for machine learning
Audio Transcription
Transcribe natural spoken language into text for data training
Text Annotation
Add structural and linguistic metadata to text
Video Annotation
Tag and track objects in video frames
Sentiment Analysis
Extract sentiment and insights from textual data
Lidar Annotation Outsourcing
Annotate Lidar spacial datasets for autonomous vehicles
Keypoint Annotation
Train your datasets with precise keypoints with unparalleled accuracy
Bounding Box
Annotate boxes to locate and identify objects in training images
Object Recognition
Identify objects in images or videos for machine learning
PROUD OF OUR TEAM
Meet our specialists team. Most of our employees are young top-talent in the Philippines and Indonesia, international tech labor hubs that nurture an ambitious, non-entitled youth deeply motivated by two core values rooted in their culture: career and family.
Our vision is to create a rich fabric of opportunities to grow our team’s careers and to sustainably support their families. This is essential in fast-developing societies where the aspirations of most families rest on the talent of the young and their careers in the new tech economy.
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Data Labeling Services Pricing
- Full-time dedicated annotators
- Complimentary QA audits
- Custom shifts or 24/7
- High accuracy
- Instant scalability
- Priority projects available
We reinvented the outsourcing model with flexibility in mind.
We set full-time teams and work on one-time projects of all sizes.