Data Annotation Services for AI/ML
Artificial intelligence (AI) and deep learning technologies are powering the next wave of innovation. Global enterprises are increasingly integrating self-learning AI/Machine learning models into their ecosystems to vastly improve operational efficiency, augment human capability, and positively impact the lives of customers. But for any machine-learning (ML) model to succeed, vast volumes of meaningful data are required to ‘train’ the model through a repetitiour-investment-ai-ml.jpg
Scale your models with a dedicated annotation service
At Infosys BPM, our data annotation service helps client data science teams build high-quality ‘training data’ for AI at scale, using a platform plus human-in-the-loop annotation service model, which saves time and resources for the teams and focuses on strategic priorities like refining and improving the AI/machine learning model itself. Our proven annotation service model leverages the power of human intelligence (humanware) and automation capability (software) to continuously churn out high-quality training datasets at scale for machine learning training and evaluation.
Proven ML annotation success across global enterprises
We work with several marque brands across the globe in their Al/Machine learning journey and support use cases for several key clients, such as:
-
Autonomous driving and computer vision:
HD image and point cloud data annotations for a global technology company -
Virtual assistant devices:
NLP annotation service and audio grading for a US-based hi-tech leader -
Customer support:
Conversation generation, categorisation, and intent tagging for a leading US-based telecommunications major , leveraging our data annotation service -
Mining (autonomous trucks):
Drone image segmentation and feature extraction for an Australian mining giant.
Infosys BPM supports AI/ML use cases for the following sectors:
CPG
Retail
Media
Rail Transport
Oil & Gas
Insurance
Healthcare
Financial Services
We are experienced in handling image annotations, work packages, and audio files for clients across the globe, which include:
- 28+ million work packages managed per year
- 150+ million image annotations handled per month
- 1.2+ million audio files processed per month
Accelerating AI/ML projects through a hybrid model
Our agile operating model enables us to seamlessly work across different annotation platforms in a platform-agnostic way, whether leveraging client-developed in-house tools, open source platforms, or third-party platforms. Here is an overview of the data annotation process that is typically followed for creating training data for machine learning models.
Our tie-ups with industry-leading training data platforms allow us to combine human capability with state-of-the-art intelligent automation to increase speed to market and deliver >98% accurate training data output through our data annotation service.
Our annotation service and labelling capabilities span several areas, such as:
Text
Tag and classify for NLP and search optimisation use cases
Entity Tagging | Linking |
Classification | Sentiment Tagging
Image
Classify and segment images for computer vision use cases
Bounding Box | Segmentation |
Polygons | Classification
Audio
Transcribe, annotate, and grade speech and audio use cases
Transcription | Grading |
Classification | Sentiment Tagging
Video
Annotate key frames and moving objects in a video format
Bounding Box | Segmentation |
Polygons | Key Points
Sensor data
Annotate data from sensors
and loT devices
Lidar Time Series Tagging |
Pattern Tagging | 3d Point Cloud
Improve efficiency with AI/ML models
Insights on data annotation services
Success Stories
Bringing values to businesses through our products and services
Case Study
Case Study
Challenges and solutions for annotation services
We combine intelligent automation with human-in-the-loop validation by subject matter experts to guarantee over 98% accuracy for every annotation service project. This rigorous quality control ensures our data annotation service delivers reliable, bias-free training datasets for complex enterprise models. Ultimately, this precise ml annotation reduces costly retraining cycles and accelerates your deployment timelines.
Security is foundational to our annotation service, which is why we strictly adhere to enterprise-grade compliance standards like ISO, SOC 2, and GDPR. We utilize secure infrastructure and a dedicated, in-house workforce rather than crowdsourcing to completely protect your proprietary data. This ensures your ai annotation service projects are executed with maximum privacy and risk mitigation.
Yes, our scalable operating model is specifically designed to rapidly process millions of complex data points, including computer vision, NLP, and 3D sensor data. Whether you require an ongoing data annotation service or highly specialized ml annotation, we dynamically adjust resources to meet your exact volume requirements. This allows our annotation service to act as a seamless, high-throughput extension of your internal data science team.
Absolutely, we assign highly trained subject matter experts to ensure deep contextual accuracy for highly regulated industries like healthcare, finance, and autonomous driving. By leveraging professionals who understand industry-specific nuances, our ai annotation service effectively resolves edge cases that automated tools frequently miss. This expert-driven data annotation service guarantees your machine learning models are trained on precise, reliable information.
We operate in a completely platform-agnostic manner, enabling our team to seamlessly work within your proprietary in-house tools or industry-leading third-party platforms. Our annotation service can export structured training data into any required format, ensuring immediate compatibility with your infrastructure. This flexibility means our ml annotation deliverables integrate flawlessly into your existing machine learning pipelines without friction.
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