We build teams of data labelers to process large training datasets for AI model development. Our in-house specialists cover different verticals, including self-driving, healthcare, energy, transportation, entertainment, and more. We achieve the highest quality through detailed labeling guidelines, expert involvement, and proven QA techniques such as quality audits and double-pass annotation. We are equipped to handle both short-term projects and recurring volumes of data.
Our commitment to data quality is reflected in every aspect of our operations. We meticulously select labelers best suited for each type of training data and ensure that our team structure—comprising Labelers, Team Leads, Quality Assurance Specialists, and Project Managers—is optimized to deliver unparalleled data integrity without sacrificing productivity. Over the years, we have consistently refined our QA audit processes and enhanced our training programs, focusing on achieving the highest data quality.
Our QA Scorecards are continuously updated through iterative improvements, informed by what we've learned from handling client-specific edge cases. This ongoing refinement process includes retraining our annotators and linguists based on precise guidelines tailored to meet evolving needs. BUNCH is supported by a seasoned team of high-touch Project Managers who bring extensive experience with ML models to our projects.
Our entire organization operates under a single, shared mantra: Data Quality. This guiding principle ensures that every piece of data we handle upholds the strictest standards of accuracy and reliability.
Our scalable teams efficiently handle data labeling projects of any magnitude—from thousands to billions of data points—tailored to the diverse needs of the AI and ML industries. We ensure rapid response and adaptability by structuring our teams from compact units for smaller projects to extensive groups for large-scale operations. Our approach includes maintaining a large pool of experienced annotators who can be mobilized within days, facilitating quick scalability.
We also offer full-time teams with specified numbers of FTEs for long-term projects, providing a cost-efficient solution for generating substantial volumes of training data. This strategy allows us to effectively manage continuous large-scale needs and volume surges, ensuring high-quality data output.
Categorize and label objects within images
Annotation of segments in images for machine learning
Transcribe natural spoken language into text for data training
Add structural and linguistic metadata to text
Tag and track objects in video frames
Extract sentiment and insights from textual data
Annotate Lidar spacial datasets for autonomous vehicles
Train your datasets with precise keypoints with unparalleled accuracy
Annotate boxes to locate and identify objects in training images
Identify objects in images or videos for machine learning
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.
We set full-time teams and work on one-time projects of all sizes.