Cognizant & Nvidia: A Partnership to Scale Enterprise AI
As organisations move towards large-scale, production-ready AI systems, they face the pressure to demonstrate tangible returns on their investments.
Part of the key to this investment success lies in firms forming partnerships with AI hardware providers to create end-to-end solutions that bridge the gap between technological capability and business value.
These collaborations address the complex requirements of enterprise AI deployment, which demands not only advanced models but also robust infrastructure, industry expertise and integration with existing systems.
A recent such partnership is Cognizant with Nvidia – aiming to focus on five key areas including:
- The development of enterprise AI agents
- Industry-specific large language models (LLMs)
- Enhanced infrastructure for AI deployment
Cognizant will integrate Nvidia's AI technology into its proprietary Neuro AI platform to provide comprehensive solutions across different sectors to help businesses transition from experimental AI applications to large-scale implementations.
Cognizant Neuro AI platform: Integrating Nvidia technology for enterprise-wide implementation
Cognizant is working with global clients to help them implement AI solutions efficiently by leveraging its industry experience and AI ecosystem.
This ecosystem encompasses infrastructure, data, models and agent development powered by Cognizant's proprietary platforms and accelerators.
The company reports that client engagements utilising Nvidia AI technology are already underway across various industries, with a focus on enabling business growth and transformation.
“We continue to see businesses navigating the transition from proofs of concept to larger-scale implementations of enterprise AI," says Annadurai Elango, President of Core Technologies and Insights at Cognizant.
“Through our collaboration with Nvidia, Cognizant will be building and deploying solutions that accelerate this process and scale AI value faster for clients through integration of foundational AI elements, platforms and solutions.”
Nvidia's involvement strengthens Cognizant's ability to deliver specialised AI applications that can address specific business challenges – the partnership demonstrating the growing importance of hardware-software integration in enterprise AI deployments.
“From models to applications, enterprise AI transformation requires full-stack software and infrastructure with access to domain-specific data,” says Jay Puri, Executive Vice President of Worldwide Field Operations at Nvidia.
“The Cognizant Neuro AI platform is built with Nvidia AI to deliver specialised LLMs and applications to ready businesses for the era of AI with reasoning agents and digital twins.”
Cognizant's multi-agent systems enhancing industry-specific AI applications
A central component of the partnership is Cognizant's Neuro AI Multi-Agent Accelerator, which will run on Nvidia NIM microservices – a set of pre-built software components that can be assembled to create AI applications.
This framework will enable clients to build and scale multi-agent AI systems, which are networks of AI entities that can work together to perform complex tasks.
These systems will also support adaptive operations, real-time decision-making and personalised customer experiences.
Clients will be able to create and orchestrate agents using a low-code framework – a development environment that requires minimal programming knowledge – or utilise pre-built agent networks for enterprise functions and industry-specific processes.
Furthermore, Cognizant is developing a modular agent architecture that allows for adaptable design to meet evolving business needs – including pre-built integrations with security safeguards and human oversight mechanisms to ensure responsible AI use.
The company plans to offer industry-specific agents for processes such as insurance claims underwriting, appeals and grievances systems, automated supply chain management and contract management.
Cognizant with Nvidia NeMo: Industry-specific LLMs
Cognizant is additionally developing industry-oriented large language models – AI systems trained on vast datasets to understand and generate human-like text – powered by Nvidia NeMo and Nvidia NIM.
These models are customised to address the unique requirements of different sectors.
One example is a fine-tuned language model (LM) for healthcare administrative processes.
- Cognizant's Neuro AI Multi-Agent Accelerator enables rapid creation and scaling of multi-agent AI systems
- Industry-specific LLMs tailored for sectors like healthcare
- Digital twin solutions for smart manufacturing combines synthetic data generation and physical AI simulation
This system leverages Cognizant's domain expertise to enhance medical code extraction – the process of identifying and categorising medical conditions and procedures for billing and analysis.
According to Cognizant's internal benchmarking, the model has demonstrated effectiveness in:
- Reducing effort by 30-75%
- Improving coding accuracy by 30-40%
- Accelerating time to market by 40-45%
The healthcare model aims to support higher accuracy, reduced errors and improved compliance with healthcare data regulations such as HIPAA and GDPR.
Nvidia Omniverse: Accelerating Cognizant’s smart manufacturing and digital twins
Another focus area is industrial digital twins – virtual replicas of physical systems that can be used for simulation and analysis.
Cognizant's smart manufacturing and digital twin offerings, accelerated by Nvidia Omniverse, aim to drive digital transformation in manufacturing operations and supply chain management.
These capabilities will assist clients in enhancing plant layout and process simulations with real-time insights and predictive analytics – as the technology enables integration of data from various sources, allowing clients to simulate scenarios and identify solutions to operational issues.
Cognizant's infrastructure for AI, powered by Nvidia, will provide clients with access to GPU computing resources through what Cognizant calls a “GPU as a Service” model, along with secure and managed infrastructure – ensuring that AI models can be deployed across different environments, including cloud, data centres or edge computing locations.
In one implementation for a large healthcare client in the US, Cognizant reports that its infrastructure for AI resulted in a 2.7x cost efficiency improvement and a 1.8x enhancement in the performance of Spark workload – a framework for large-scale data processing.
“As we enter the era of AI industrialisation, enterprises are seeking to accelerate the value velocity of their AI investments – focusing on outsized economic impact, agentic-led workflow transformation and industry-specific deployments,” says Nitish Mittal, Partner at Everest Group.
“Cognizant's deepening partnership with Nvidia signals the right trajectory for forward-thinking enterprises aiming to unlock breakthrough value in the AI era.”
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