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AutomotiveOne Governed Operating Layer for Enterprise Agentic AI.
ZBrain is the meta-harness for your agentic AI ecosystem: the control layer that brings agents and agentic solutions built on ZBrain or other platforms into the same registry, policy layer and audit framework. ZBrain also provides a structured path across the solution lifecycle, with governance embedded throughout, from use case analysis and technical design through solution development and deployment.
- Governance across enterprise, functional and application levels
- Governance for agents built on Azure AI Foundry, AWS Bedrock and Google Vertex AI
ZBrain Governance Layer
The runtime governance layer that evaluates governed agent actions.
Each agent action is evaluated against the applicable governance controls before execution.
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Agentic AI is Reaching Production Faster Than Governance.
As agents access data, invoke tools, execute workflows and update systems, critical governance decisions around permissions, approvals, accountability and operational controls need to be defined before production.
The challenge is not a shortage of ideas. It is establishing the context and governance requirements that enable use cases to seamlessly move through technical design, build and governance. Without this clarity, even promising initiatives can stall or get canceled.
of agentic AI projects will be canceled by the end of 2027 driven by cost, unclear business value and inadequate risk controls
of organizations have fully embedded AI governance while 93% already use AI
of organizations that suffered an AI-related breach lacked proper AI access controls
ZBrain is not just where agentic solutions are built.
It is where they are governed for production.
How ZBrain Helps: One Governance Layer, Three Levels of Control
ZBrain offers a single governed path from use-case analysis to technical design, solution build and runtime execution. ZBrain Governance, the core layer of the platform, provides enterprise, functional and application-level controls for deployed agentic solutions.
Enterprise governance
Organization-wide policies every governed solution inherits: identity standards, approved models and tools, access boundaries, data rules, security requirements, cost controls and audit standards.
Functional governance
Inherits enterprise-level controls and adds or tightens function-specific controls for data access, approved models and tools, budgets, use cases, compliance requirements and approval chains.
Application governance
Applies inherited enterprise and functional controls to individual solutions and agents, with runtime policy gates, confidence thresholds, approval requirements and tamper-evident audit trails.
ZBrain Extends Governance Across the Agentic AI Ecosystem
Govern agents across platforms
Agents built on Azure AI Foundry, AWS Bedrock, Google Vertex AI, LangGraph, Google ADK, Microsoft Semantic Kernel and Microsoft Agent Framework can be onboarded into ZBrain's governance layer without requiring teams to rebuild existing agents.
Operate through one governance view
Each governed agent can be registered to capture its purpose, owner, identity, approved tools, permitted data sources, autonomy level, access scope and lifecycle status. Policies, approvals, exceptions and escalations can be traced through one audit view.
Deploy in the client's environment
ZBrain runs in the client's preferred cloud environment, tenant, region and security perimeter. It works with enterprise-selected models, frameworks and endpoints, using keys controlled by the client.
From Use Case to Governed Solution, on One Platform
Beyond governing the agentic AI ecosystem, ZBrain transforms a use case from analysis into a fully deployed, production-ready agentic solution. Each stage adds context, technical design detail, and build logic, and every stage inherits the governance layer.
ZBrain Analyzer
With ZBrain Analyzer, AI agents engage functional team members to collect and structure the context of the selected use case. That analysis gives ZBrain Design the clarity required to produce a build-ready technical design.
A fully analyzed use case with the context required for technical design.
ZBrain Design
ZBrain Design creates a build-ready technical design for the selected use case. It generates the BRD, functional requirements, user journeys, architecture, workflow logic, data details, integration context and governance considerations needed before development begins. Stakeholders can review, refine and collaborate on the technical design before it moves into build.
A build-ready technical design with the details required for development.
ZBrain Solution Builder
ZBrain Solution Builder provides a conversational interface for turning the technical design into a working agentic solution. Teams can create workflows, configure agents, connect systems, add guardrails, define approval points and generate the user interface. They can iterate on the solution, refine agent behavior, adjust workflows, validate outputs and prepare it for deployment in the client's preferred cloud environment.
A production-ready agentic solution with workflows, agents, integrations, controls and UI.
ZBrain Governance
Every solution built on ZBrain progresses through a unified governance framework from analysis through production, with policies, approvals, and runtime controls maintained throughout the lifecycle.
A deployed agentic solution ready to operate within defined governance controls.
Runtime Governance vs. Traditional AI Governance Platforms
Focus on AI governance, visibility, compliance, and reporting.
Extends governance into the runtime, where AI agents execute work.
Maintain an inventory of AI applications and governance assets.
Maintains a live registry of governed agents, capturing each agent's owner, approved tools, permitted data sources and operating scope.
Map AI systems to governance frameworks and compliance requirements.
Maps compliance requirements to enforceable governance rules, with audit trails providing evidence of governed execution.
Primarily provides governance through policy management, monitoring, and audit processes.
Brings governance into the execution path, evaluating AI actions against runtime policies.
Support governance through policies, controls, and oversight.
Can allow, audit, or block actions based on runtime policy.
Govern AI systems throughout their lifecycle.
Carries governance from use case analysis and technical design through build, deployment and runtime.
Book a Demo to Learn How ZBrain Governs Agentic AI
Learn how ZBrain governs deployed agents at runtime and applies the same governed path to analyze use cases, create technical designs and build agentic solutions.
