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Simplify AI complexity. Achieve scale.

Companies across industries are turning to AI to optimize operations, enhance customer experiences, create new products and services and gain unprecedented insights into their business operations.

Yet quickly building and deploying AI-infused solutions—including applications, machine learning operations (MLOps), data pipelines, knowledge bases and agentic AI systems—requires navigating complexity at every layer of the AI stack. Talent shortages, fragmented tooling and operational challenges in deploying AI at scale are preventing many proofs of concept efforts from reaching production.

Cognizant Neuro AI Engineering simplifies AI implementation, infrastructure management and operations, enabling enterprises to develop high quality, more resilient AI solutions, faster.

Its full-stack design incorporates best practices from the start, while automated MLOps eliminate risks and inefficiencies through proactive checks for guardrails, AI security, compliance and quality assurance. 

"By 2027, 75% of business applications will incorporate generative AI features, up from less than 5% today."*

Platform benefits and features

Accelerated AI innovation and time to market

Enable rapid prototyping with prebuilt components, significantly reducing the time from concept to production.

Greater AI solution quality and reduced risk

Embed best practices and governance across the AI stack to deliver higher quality, robust AI solutions while proactively mitigating compliance and security risks.

Improved business agility and adaptability

Enable quick and cost-effective experimentation with new AI technologies/models and incremental scaling using a composable architecture, multi-provider support and continuous deployment capabilities. 

Strategic visibility and governance

Centralize visibility and control over AI models, infrastructure, datasets and usage patterns across the organization with a full-stack approach and single interface.

AI multi-agent capabilities

Support a choice of popular third-party agentic AI frameworks such as CrewAI, AutoGen, and AWS Bedrock as well as Cognizant’s own Neuro® AI Multi-Agent Accelerator—enabling multi-agent interoperability and integration.

Responsible AI features

Use a modular and extensible approach including predefined prompts, templates and fine-tuned LLM log analyzers to ensure responsible AI deployment.

Interoperability across infrastructure providers

Use a template-based approach with pluggable modules to facilitate switching between cloud (e.g., AWS, Azure, GCP) or private infrastructure (e.g., NVDIA) with relative ease and lower risks.

Observability and metrics

Provide consistent tools for observability, performance tracking, and estimating response times and costs across every environment.

Partner with us

Leaders in modern engineering

Cognizant’s deep experience supporting enterprise-scale systems modernization and innovation makes us an ideal partner for next generation engineering.

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Deep industry domain expertise

Our teams bring extensive industry and functional domain expertise that help drive business process and workflow innovation.

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At the forefront of AI-powered automation

We work with hyperscalers and clients every day to build the future of enterprise-grade AI-powered automation, and we’re using this expertise to redefine software engineering.

Let us show you

For a demo and to learn how Neuro AI Engineering can help your organization build better AI systems, faster, please share details below. 

*Gartner®, Generative AI will radically change the nature of custom apps, By Van Baker, 24 January 2025.

GARTNER is a registered trademark and service mark of Gartner, Inc. and/or its affiliates in the U.S. and internationally and is used herein with permission. All rights reserved.