Cognizant has introduced developments constructed on NVIDIA synthetic intelligence (AI) geared toward accelerating the cross-industry adoption of AI expertise in 5 key areas: enterprise AI brokers, industry-specific giant language fashions (LLMs), digital twins for good manufacturing, foundational infrastructure for AI, and the capabilities of Cognizant’s Neuro AI platform to combine NVIDIA AI expertise and orchestrate throughout the enterprise expertise stack.
Cognizant is working with international purchasers to assist them scale AI worth effectively, utilizing in depth {industry} expertise and a complete AI ecosystem comprising infrastructure, knowledge, fashions and agent improvement powered by proprietary platforms and accelerators. NVIDIA AI performs a key function in Cognizant’s AI choices, with lively consumer engagements underway throughout industries to allow development and enterprise transformation.
“We proceed to see companies navigating the transition from proofs of idea to larger-scale implementations of enterprise AI,” mentioned Annadurai Elango, the president of core applied sciences and insights at Cognizant. “By our collaboration with NVIDIA, Cognizant might be constructing and deploying options that speed up this course of and scale AI worth sooner for purchasers via integration of foundational AI parts, platforms and options.”
“From fashions to purposes, enterprise AI transformation requires full-stack software program and infrastructure with entry to domain-specific knowledge,” mentioned Jay Puri, the chief vp of worldwide discipline operations at NVIDIA. “The Cognizant Neuro AI platform is constructed with NVIDIA AI to ship specialised LLMs and purposes to prepared companies for the period of AI with reasoning brokers and digital twins.”
At NVIDIA GTC 2025, Cognizant offered its intent to ship providing updates throughout the next 5 areas:
- Enterprise AI agentification powered by Cognizant Neuro AI Multi-Agent Accelerator: Working on NVIDIA NIM microservices, this framework will assist allow purchasers to quickly construct and scale multi-agent AI methods for adaptive operations, real-time decision-making and personalised buyer experiences. With these frameworks purchasers are higher positioned to create and orchestrate brokers utilizing a low-code framework or use pre-built agent networks for numerous enterprise capabilities and industry-specific processes reminiscent of gross sales, advertising and marketing and provide chain administration. The frameworks additionally enable purchasers to simply combine third-party agent networks and most LLMs.
- Constructing multi brokers for scale: Cognizant works to reinforce enterprise operations via using multi-agent methods and integration with NVIDIA NIM, NVIDIA Blueprints and NVIDIA Riva speech AI. The corporate might be growing a future-proof agent structure that helps modular and adaptable agent design to fulfill evolving wants and the long-term viability and flexibility of AI options. This contains pre-built integrations with safety guardrails and human oversight. This strategy goals to allow enterprises to develop and deploy market-ready purposes tailor-made to their particular wants utilizing the pre-built agent catalog. Examples embrace {industry} brokers reminiscent of insurance coverage claims underwriting multi-agent methods, appeals and grievances multi-agent methods, automated provide chain multi-agent methods and contract administration multi-agent methods.
- Trade LLMs: Cognizant is growing industry-oriented LLMs powered by NVIDIA NeMo and NVIDIA NIM. These options are tailor-made to fulfill the distinctive wants of various industries and construct on Cognizant’s deep {industry} experience to drive innovation and enhance enterprise outcomes. For instance, Cognizant has developed a fine-tuned language mannequin to remodel healthcare administrative processes. This method will use Cognizant’s area experience and NVIDIA expertise to assist improve medical code extraction and assist larger accuracy, diminished errors and higher compliance with HIPAA and GDPR requirements. It’s designed to assist purchasers reduce prices, lower latency, enhance income cycle administration and assist assist correct danger adjustment. In inside Cognizant benchmarking, the mannequin has demonstrated effectiveness in decreasing effort by 30-75%, boosting coding accuracy by 30-40%, and accelerating time to market by 40-45%.
- Industrial digital twins: Cognizant’s good manufacturing and digital twin choices, accelerated by NVIDIA Omniverse, will purpose to drive digital transformation by combining NVIDIA Omniverse’s artificial knowledge era, accelerated computing, and bodily AI simulation applied sciences to deal with challenges in manufacturing operations and provide chain administration. These capabilities might be designed to help purchasers in enhancing plant format and course of simulations with real-time insights and predictive analytics, whereas additionally supporting improved operational effectivity and optimised plant capital expenditure. This providing allows integration of numerous knowledge from purposes, methods and sensors with artificial knowledge, permitting purchasers to simulate numerous eventualities and discover options to points within the plant. Moreover, by constructing the required digital infrastructure, together with IT methods and expert personnel, Cognizant’s choices can be utilized to create and handle digital twins for large-scale methods, reminiscent of factories, good grids, warehouses or whole cities, with precision and effectivity.
- Infrastructure for AI: Implementing AI successfully requires strong AI infrastructure and knowledge ready for AI. Cognizant’s infrastructure for AI, accelerated by NVIDIA, will present purchasers entry to NVIDIA AI expertise by way of “GPU as a Service”, together with safe and managed infrastructure. This helps make sure that AI fashions might be run in numerous environments, together with the cloud, knowledge centres or on the edge. Moreover, Cognizant intends to make use of NVIDIA RAPIDS Accelerator for Apache Spark to assist purchasers speed up knowledge pipelines for AI implementations, facilitating environment friendly and scalable operations. In a single instance implementation for a big healthcare consumer within the U.S., use of Cognizant’s infrastructure for AI resulted in a 2.7x value effectivity enchancment and a 1.8x enhancement within the transformation efficiency of their Spark workloads.
Based on Sid Nag, the vp analyst at Gartner, et al., “Providing agentic AI platforms allows enterprises to construct, handle and scale AI brokers. Agentic AI platforms that combine orchestration, real-time studying, governance and knowledge safety capabilities will differentiate suppliers within the subsequent evolution of AI and automation. New orchestration options will emerge as enterprises make use of a number of brokers and people brokers develop into extra autonomous and interactive. Agent orchestration will characterize a brand new class of software program. The best orchestration options will span a number of brokers from totally different software program suppliers.”
“As we enter the period of AI industrialisation, enterprises are searching for to speed up the worth velocity of their AI investments—specializing in outsized financial influence, agentic-led workflow, and industry-specific deployments,” mentioned Nitish Mittal, a companion at Everest Group. “Cognizant’s deepening partnership with NVIDIA indicators the best trajectory for forward-thinking enterprises aiming to unlock breakthrough worth within the AI period.”
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