TRUSTED AI AT SCALE
Neuro AI Trust
Centralized command center for real-time visibility and proactive risk evaluation across every model, agent and application
<h3>Stay in control of AI in production</h3>
<p>As AI moves into production, the question shifts from what models can do to whether enterprises stay in control of their actions. Neuro® AI Trust addresses these challenges with a supervisory, agentic control layer that oversees and manages AI systems.</p>
<p>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.</p>
<blockquote><i><b>“Traditional AI governance models built on periodic process audits and static policies can’t keep up with nondeterministic, modern AI architectures, such as retrieval-augmented generation and autonomous agent-based systems.”<br>
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—Sumit Agarwal, VP analyst at Gartner <a href="https://www.ciodive.com/news/AI-governance-gartner-sumit-agarwal/816720/">Source CIO Dive</a></i></blockquote>
Key benefits
Explore platform capabilities
Powered by specialized multi-agent networks, Neuro AI Trust enables continuous oversight and control across enterprise AI systems.
- Observability, monitoring and incident prediction
- Guardian agents for system-wide oversight
- Policy management from design to runtime
- Dynamic governance without code changes
- Human escalation and kill switch
- Audit-ready records and full traceability
Observability, monitoring and incident prediction
A trust score and full lifecycle visibility show how models and agents behave, including cost, sustainability and agent interactions. The platform detects drift and coordination risks early and predicts incident likelihood, so teams can act before an issue becomes an incident.
Guardian agents for system-wide oversight
A dedicated multi-agent system 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 miss. Guardian agents detect and flag; policies and controls hold the limits.
Policy management from design to runtime
Policies are available at design time so controls can be built into applications from the start. At runtime, interactions are evaluated against regulatory frameworks including NIST AI RMF, the EU AI Act, the OECD AI Principles and ISO/IEC 42001, as well as custom internal policies.
Dynamic governance without code changes
Policies, policy packs and risk thresholds are loaded dynamically at runtime, so compliance, legal and risk teams can update controls immediately, without depending on engineering or code releases.
Human escalation and kill switch
Higher-risk or ambiguous decisions can be paused and routed to a human reviewer with the full context needed to approve, reject or request more information. A native kill switch lets authorized operators stop an AI application.
Audit-ready records and full traceability
Every AI interaction is logged and can be reconstructed in full through replay views, giving operators and auditors a complete record of what happened, why, which policy applied and how the controls responded at each step.
Industry applications
Built on the Cognizant Trust framework
The Cognizant Trust™ framework provides a practical structure for turning our responsible AI standards into real-world impact across the full AI lifecycle. Neuro AI Trust is grounded in the Trust framework, ensuring AI systems continuously perform in a transparent, fair, safe, accountable and reliable manner.
Latest thinking
For a deeper dive into responsible AI and ethics...
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