Cognizant is a data and AI model training partner long trusted by major digital native pioneers to train some of the world’s most advanced AI/ML models.
Cognizant (NASDAQ: CTSH ) today announced the launch of AI Training Data Services, a new offering to help organizations build, fine-tune, and deploy AI models rapidly and at scale. Leveraging its deep experience as a data and AI model training partner for select digital-native pioneers, Cognizant also provides its expertise to clients across the Global 2000 to accelerate AI innovation.
The market’s need for clean, relevant training data is critical for companies developing AI-powered applications and seeking to deploy generative and agent-based AI. The limited availability of large, accurately annotated datasets can pose a significant bottleneck for training machine learning models, particularly for large language models (LLMs) and computer vision systems. Multimodal data, which includes text, images, audio, and more, is particularly valuable because it enables models to handle complex scenarios that require context from multiple data forms.
Cognizant’s AI Training Data Services are a strategic offering that enables organizations to rapidly build, fine-tune, validate, and deploy AI models at scale, in accordance with the organization’s internal governance and oversight. They combine expertise in data engineering and AI training with deep domain and industry knowledge to transform multimodal data into high-quality inputs for machine learning and generative AI models. These services include data annotation, model adaptation and augmentation, and data governance, and are designed to enable organizations to accelerate time to market, increase model accuracy and performance, and reduce costs.
For years, Cognizant has helped leading digital companies train some of the world’s most advanced AI models. The company has worked with pioneers in technology, healthcare, automotive, media, and retail. Cognizant’s more than 10,000 experts have annotated and quality-checked billions of data points and millions of data labels for every major modality—including speech, 2D/3D images, video, and Light Detection and Ranging (LiDAR), often enriched with geographic metadata for additional accuracy. This expertise enables Cognizant to create highly accurate, specialized datasets for healthcare, automotive, media, digital marketing, and more.
“At Cognizant, we are committed to helping our clients accelerate their AI innovations at scale. With the launch of AI Training Data Services, we are furthering this commitment and providing companies with the high-quality, multimodal data they need to develop sophisticated AI solutions,” said Ravi Kumar S. , CEO of Cognizant . “By leveraging this specialized capability, developed jointly with digital innovators, we are taking a significant step forward in supporting AI transformation for our G2000 clients across multiple industries.”
Cognizant’s AI Training Data Services offer several core features, such as:
- Comprehensive data annotation and curation, including:
- Multimodal data labeling that enables expert annotation and curation of multimodal data (e.g., text, images, audio, video) for high-fidelity AI training, from content understanding to conversational AI.
- Data for AI model adaptation and improvement, including:
- Supervised fine-tuning data: Carefully curated datasets for fine-tuning LLMs and Foundation Models.
- Reinforcement Learning from Human Feedback (RLHF): High-quality human feedback for RLHF, designed to help customers align the AI model’s behavior with human preferences and values, under the customer’s supervision.
- Red Teaming Data for Robustness: Compilation of data sets to support red teaming exercises aimed at identifying potential vulnerabilities and points of failure.
- Enterprise-level AI evaluation and governance, including:
- Agent solutions and contextual technical data: Specialized data services for building, refining, and evaluating AI agent solutions under customer-defined parameters.
- LLM model evaluation data and reporting: Robust data to assess LLM performance against various criteria.
- Enterprise AI Implementation: Deployment of AI models in the customer’s Virtual Private Cloud environment, designed to support enterprise-grade data security, privacy, and control.
“Companies are eager to operationalize AI, but many are held back by data debt—a persistent burden of fragmented, poor-quality, or inaccessible data that limits the development of effective AI models,” said Saurabh Gupta , President, Research & Advisory Services at HFS Research. “Cognizant addresses this challenge by consolidating its full range of services—business services, IT expertise, engineering excellence, and ecosystem partnerships—into a lean, industry-specific solution. Combining deep domain knowledge with advanced data development and training capabilities, Cognizant’s AI training data services exemplify the services-as-software approach to help companies close the data readiness gap and remain competitive in an AI-driven world.”
“Companies today are seeking to deploy generative and agent-based AI at scale. These technologies promise to transform business models by enabling a much higher degree of end-to-end automation and, therefore, more efficient and effective operations,” says Anil Vijayan, Partner at Everest Group. “As these scale, the need for rich and diverse data increases, accelerating AI model creation, improving model accuracy, and supporting regulatory compliance. Cognizant’s AI Training Data Services, with their track record of success, are of great value in this space.”
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