Enterprise Data Labeling Services for AI & ML Models
We offer robust Enterprise Data Labeling Services (EDLS) through our highly skilled workforce for ensuring cost-effective, scalable, and quality labeling solutions. Our EDLS helps you save time and divert your focus to more strategic initiatives.
Our services are geared to help large organizations like yours to fine-tune as per domain specificity, ensure data quality, offer diverse annotation teams, integrate our services with RLHF, and prioritize data authenticity.
Key Features of Our Enterprise Data Labeling Services
Domain-specific Solutions via Fine-Tuning
We offer EDLS by aligning our data annotation practices as per industry requirements ranging from healthcare to finance. Our services ensure that machine learning models and analytics are built on domain-relevant data for driving superior results and actionable insights.
Data Excellence
We ensure data quality or excellence by incorporating rigorous data collection and annotation methods backed by top-tier anonymization processes. We mitigate biases, ensure data integrity, and reliability by carrying out regular audits and feedback cycles.
Diverse Annotation Teams
We leverage a diverse pool of annotators to cut across various linguistic, academic, and cultural backgrounds. This diversity translates into data that comprehensively captures global nuances making AI systems universally competent and culturally sensitive.
Reinforcement Learning with Human Feedback (RLHF)
We use RLHF to ensure our machine learning models evolve iteratively and improve with human-in-the-loop feedback. RLHF combines the computational strengths of AI with the qualitative judgments of human experts resulting in robust, refined, and resilient AI models.
Respect for Intellectual Property
Our EDLS is engineered to ensure AI models are trained on genuine and ethically-sourced data. We prioritize data authenticity and uphold the highest ethical standards to ensure that AI models are trained on genuine, ethically-sourced data, aligning technological advancements with moral responsibility.
Human-In-The-Loop For All Your Data Enrichment Needs
Our purpose remains to embrace the power of human ingenuity and technology to create 360° value for your AI & business initiatives. We provide enterprises globally with stellar quality data labeling services through a combination of human intelligence and advanced tools.
Our Data Labeling Expertise
We have a decade long industry exposure in data annotation & labeling for obtaining high-quality training data that can be deployed across industries like healthcare & diagnostics, finance & banking, security & surveillance, and much more.
We produce highly accurate and good quality training datasets to companies for providing AI and ML related services.
Data Annotation and Labeling Simplified
An integral but complex, cumbersome, and labor-intensive part of building AI training data is structuring raw datasets in a machine-readable format through appropriate annotation & labeling.
We can provide AI enterprises with well-curated, accurate, and reliable training data solutions to deploy AI in real-life systems.
Our background in AI, machine learning, and data processing makes us well-equipped to offer industry-specific workforce solutions for AI data annotation & labeling.
Reasons to Outsource your Data Annotation Services to Us
Quality Data Labels
We carry out quality assurance during our data labeling process which leads to value addition during the machine learning model testing and validation stages.
Scalable Solutions
We save you from the pain and costs involved in scaling your data labeling operations owing to growth in volume and capacity.
Cost-effective Services
We help you save costs by ensuring your data scientists are prevented from carrying out basic and repetitive work.
Domain Expertise
We have a captive pool of subject matter experts who have expertise in various domains to cater to your varied needs.
Types of Data Annotation Services
Image Annotation
This involves labeling digital images for training computer vision algorithms. It involves labeling objects in images, identifying features in images, and outlining boundaries of objects.
Techniques used by us:
Object Detection Key Point Annotation 2D Bounding Boxes Polygon Annotation 3D Cuboid Annotation Semantic Segmentation Image Classification Image Moderation Image-to-Text Transcription
Text Annotation
This involves building and optimizing AI training datasets by capturing, generating, annotating, and validating large volumes of multilingual text data.
Techniques used by us:
Classification Moderation and annotation of text data for applications in NLP Chatbots and Conversational AI
Audio Annotation
This involves attaching labels or descriptions to audio recordings to help categorize and organize the data.
Techniques used by us:
Audio Classification Event Based Time-Stamp Labeling Speech-to-Text Transcription
Video Annotation
This involves annotating video frames and sequences for computer vision to provide contextual information for algorithms and applications.
Techniques used by us:
Frame-by-Frame Video Labeling
Video Classification Event Based Timestamp Labeling Live Video Stream Monitoring Video Moderation
LiDAR Annotation
Use LiDAR Annotation services for accelerating AI integration into LiDAR models with appropriately annotated and labeled datasets.
Techniques used by us:
Object Detection & Tracking Semantic Segmentation Photogrammetric Point Clouds
Waveform Annotation
We use data annotation & labeling to segment and identify features within the waveforms. Since the waveforms of the body are indicators of a person’s health, one can get a detailed diagnostic into the vital organs using precise medical waveform annotation.
Techniques used by us:
Event Based Time-Stamp Labeling Waveform Classification Abnormality Detection
Get Us On Board
Let us contribute the best of our data annotation and labeling expertise to your computer vision-based models and AI algorithms.