Cognizant launches Neuro AI Trust platform to deliver real-time AI governance for enterprises

Cognizant Neuro AI Trust addresses enterprise AI governance gaps

Cognizant announced Cognizant Neuro AI Trust, an AI governance platform built to provide enterprises with continuous governance and real-time assurance across increasingly complex AI environments1

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. As organizations deploy multiple AI models, multi-agent networks, and autonomous applications, managing visibility and risk becomes more difficult. Traditional governance approaches built for static systems cannot keep pace with the dynamic nature of enterprise AI systems1

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. According to Gartner, organizations that deployed AI governance platforms are 3.4 times more likely to achieve effectiveness in AI governance than those that do not1

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. This reinforces the need for centralized platforms enabling continuous, real-time oversight.

Dual-layer architecture enables real-time AI governance

The AI governance platform introduces an interoperable control layer and intelligence layer purpose-built for enterprise AI oversight3

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. The control layer provides end-to-end observability across AI systems, using Guardian Agents to continuously monitor behavior, interactions and outcomes, delivering clear visibility into system health, performance, security and risk1

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. In parallel, the intelligence layer governs how these systems operate, evaluating interactions in real time and applying configured policies through centralized decisioning, guardrails and automated controls designed to align with business objectives and regulatory requirements3

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. These specialized multi-agent networks operate across distinct domains such as AI policy enforcement, risk management and governance, enabling system-wide visibility and coordinated control1

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Guardian Agents detect coordination failures across AI systems

A dedicated multi-agent system continuously monitors agent interactions across steps, tools and turns, catching coordination failures such as escalation loops, circular disputes, risky tool use and emergent patterns that single-message checks would miss3

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. The platform evaluates all AI interactions at runtime, returning permissive, warning or blocking outcomes based on configurations aligned with frameworks including NIST AI RMF, EU AI Act, OECD Principles and ISO/IEC 42001, as well as internal custom policies2

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. Continuous assurance for AI is delivered through comprehensive trust scores and full lifecycle observability, giving operators clear visibility into model behavior, agent interactions, and outcomes across the entire AI stack, including early detection of model drift and coordination risks spanning multiple agents3

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Predictive risk detection and human escalation built into platform

Cognizant Neuro AI Trust moves governance upstream, using signals from AI traces to anticipate potential policy violations earlier in the workflow lifecycle through predictive risk detection3

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. Policies, policy packs and risk thresholds are dynamically loaded at runtime, allowing compliance, legal and risk teams to update controls as requirements evolve without waiting on code releases2

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. Higher-risk or ambiguous decisions can be paused and routed to human reviewers with full context needed to approve, reject, or request more information before any action is taken3

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. Audit trails provide audit-ready records and replay views allowing operators and auditors to reconstruct captured AI interactions in detail, understanding what happened, which policy applied, and how the governance layer responded at every step3

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Platform already serves 350,000 employees internally

The Neuro AI Trust platform has been deployed internally across Cognizant's agentified intranet, serving its 350,000 employees1

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. "Neuro AI Trust was built to govern AI as it actually behaves: autonomously, continuously, and across systems that interact in ways no single policy check can anticipate. We know it is effective because we have applied it to our own AI systems," said Amir Banifatemi, Chief Responsible AI Officer at Cognizant1

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. Jennifer Hamel, Research Vice President at IDC, noted that "as agentic AI moves into enterprise operations, the constraint is no longer capability but trust," and organizations increasingly look to service providers for agentic AI platforms that combine technical integration, governed deployment and auditability as a strategic operating layer1

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. The platform integrates with Cognizant's broader AI portfolio, including the Neuro AI Multi-Agent Accelerator, reflecting the company's strategy as an AI Builder helping enterprises maintain accountability for AI in production through centralized oversight and responsible AI adoption3

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