End-to-End Data Annotation Solutions
High-Quality Training Datasets for Diverse Industries:
Advancements in Artificial Intelligence (AI) and Machine Learning (ML) technologies are the key drivers for the growing demand for data annotation solutions. Data annotation is the process of labeling datasets present in texts, images, audio, and videos. It is done to increase AI and ML models’ capabilities and help enterprises organize data and derive insights. Considering the massive volume of data generated by enterprises, it makes business sense to outsource your data labeling needs to the experts. This will allow your data scientists to spend time on important tasks such as answering questions.
Accurately labeled data helps in improving the accuracy of your ML models. AI needs to process a large volume of data and leverage ML, Natural Language Processing (NLP), and Deep Learning (DL) models to learn and evolve continuously. It follows that the more the availability of data to learn from, the better and more accurate the output of your AI tools.
LearningMate’s data annotation service makes data with specific objects recognizable for AI engines by tagging objects within textual, image, scans, and videos. Moreover, the objects are tagged in the forms and ways the target ML models need.
Accuracy and quality are two imperatives for data annotation and labeling. The annotated and labeled data help validate and train the AI and ML models and predict and validate model outcomes.
LearningMate’s Capabilities & Expertise
Enable a Seamless Data Journey
LearningMate’s next-generation cognitive data annotation and labeling services can quickly acquire quality data to train AI/ML algorithms developed by our seasoned experts to accelerate deep learning models.
Benefits
Seasoned Experts
LearningMate’s Subject Matter Experts help enterprises acquire accurate datasets from diverse sources and effectively annotate and label them. Detailed discussions with your data science teams by AI/ML-aware LearningMate experts speed up output agreements.
Scalability
With multiple years of experience, LearningMate can manage seasonal variances and accommodate high volume while ensuring quality. The availability of multi-skilled domain experts with a solid framework to check annotation quality enables scalability.
Sustained Growth & Innovation
Our experts enable you to develop training datasets for AI engines, bringing down costs and improving time efficiency.
Diverse Sources/Cross-Domain Capabilities
Our team of experts analyzes data from multiple or disparate sources. Furthermore, the team can develop AI-training data efficiently and in volumes across all sectors.
Competitive Edge
The wide gamut of variable data provides AI with copious amounts of information needed to train faster. Well-documented sampling and candidate identification strategies for annotations through collaborative discussions make this achievable. LearningMate’s team uses sophisticated tools customized for the annotation, labeling function based on decades of functional, and domain experience that capture annotations in a structure best suited for use in ML model learning.
Enhanced Data Security
Experience with delivering almost 80% of our work across clients remotely and securely is leveraged for enhanced data security. This ensures that the data formats adhere to the security policies.
LearningMate’s Types of Data Annotation
Text Annotation
LearningMate offers cognitive text data annotation services through its Data Platform, designed to allow enterprises to harness the potential information present in unstructured formats–text, image, audio, and video. Text data annotation helps machines interpret natural language. With rich experience in natural language and linguistics, LearningMate is well-equipped to handle text annotation projects of any scale. Our seasoned experts can work on various text annotation services–entity recognition, intent analysis, sentiment analysis, etc.
Annotation Services:
- Text classification
- Linguistic annotation
- Entity annotation
- Entity linking
- Sentiment annotation
- Semantic annotation
Image Annotation
LearningMate’s image annotation service classifies and labels images using captions, identifiers, and keywords as attributes of the images. The LearningMate Data Platform annotates images through various techniques–bounding box, 3D cuboids, semantic annotation, pixel-wise segmentation, polygons, image classification, and more to develop training datasets for ML models to enhance your AI engines. AI-enabled systems with human annotators strengthen the effectiveness of automating repetitive and error-prone manual activities.
Image Annotation Services:
- Bounding boxes
- 3D cuboids
- Semantic segmentation
- Polygon annotation
- Landmark annotation
- Line segmentation
Audio Annotation
Audio annotation services help label audio recordings to develop, train, and improve conversational AI, chatbots, and speech recognition AI engines. Our qualified linguists from across the globe, backed by experienced project management teams, can gather hours of multilingual audio and annotate large volumes of data to train voice-enabled applications. We also transcribe audio files to extract meaningful insights available in audio data.
Audio Annotation Services:
- Audio transcription
- Speech labeling
- Audio classification
- Multi-label audio annotation
Video Annotation
Video annotation labels video clips used to train computer vision models to detect or identify objects. The solution captures each frame and object in the video, annotates, and makes the moving objects recognizable. The combination of skill and technology offers you a comprehensively labeled dataset that is right for your business.
Video Annotation Services:
- Bounding boxes
- 3D cuboids
- Semantic segmentation
- Polygon annotation
- Key-point annotation
- Line & polyline annotation
- Frames classification
- Video transcription
Why Look to LearningMate for Data Annotation Services?
LearningMate is a leading data annotation service provider with a skilled and experienced team. We offer advanced data labeling and annotation solutions through a robust platform built on the latest technologies, hosted on the cloud, and able to deploy a client-specific platform in days. Our data annotation solution can identify and understand the sentiment in insurance documents, physician notes, pathology reports, financial statements, use cases, and more.
LearningMate’s data annotation solution can reduce your expenses and other hassles by managing the annotation workforce.
Dedicated & Seasoned Teams:
- 500+ collaborators for data creation, labeling, and QA
- 80+ credentialed project management team
- 60+ experienced product development team
- 40+ talent pool sourcing and onboarding team
Process:
The highest process efficiency is assured with:
- Certification-like, Robust 6 Sigma Stage-Gate process
- Dedicated team of 6 Sigma black belts – key process owners and quality compliance
- Continuous improvement and feedback loop
Platform:
The patented platform offers the following benefits:
- Web-based end-to-end platform
- Impeccable quality
- Faster TAT
- Seamless delivery
Why Outsource Data Annotation for Your AI/Data Science Projects
Dedicated Team
Data scientists spend nearly 80% of their time in data cleaning, classification, and preparation. By outsourcing your data labeling needs, your team of data scientists can focus on continuing the development of robust algorithms leaving the tedious part of the job to us.
Better Quality
Dedicated domain experts who annotate day-in and day-out will — any day — do a superior job compared to a team who needs to accommodate annotation tasks in their busy schedules, resulting in better output.
Scalability
ML models need to label large amounts of data, requiring enterprises to dedicate more resources. A reliable data annotation service provider like us offers domain experts who dedicatedly work on your data labeling projects and can scale operations as your business grows.
Eliminate Internal Bias
Most AI/ML models fail because data acquisition and annotation unintentionally introduce bias, skewing the outcome and impacting accuracy. However, the data annotation and labeling vendor does better at annotating the data for improved accuracy by eliminating assumptions and bias.