# ZBrain A governance-first enterprise AI platform for building, deploying, and overseeing agentic solutions. - Findings24: - Website: - Pricing: Freemium - Categories: AI Agent Builder, AI Agent Infrastructure ## What is ZBrain? ZBrain is an enterprise AI platform for designing agentic solutions and governing them through deployment and runtime. It provides a shared control layer for solutions built in ZBrain as well as agents developed with supported external frameworks. Teams can move from use-case analysis through technical design and solution building, with governance requirements incorporated along the way. The platform organizes controls at enterprise, functional, and application levels, covering areas such as approved tools, access boundaries, approvals, runtime policies, and audit trails. ZBrain is designed to run in a client-selected cloud environment, tenant, and region, using enterprise-selected models and endpoints. ## What can ZBrain do? ### Governance at three levels Set organization-wide standards, function-specific controls, and application-level runtime rules. Controls can address identities, approved models and tools, data access, approvals, confidence thresholds, and audit requirements. ### Use-case analysis and technical design ZBrain Analyzer gathers and structures use-case context, including ownership, dependencies, and risks. ZBrain Design turns that context into build-ready technical design materials such as requirements, user journeys, architecture, and workflow logic. ### Conversational solution building Solution Builder uses technical designs or uploaded requirements to propose agent roles, responsibilities, workflows, integrations, and test data. Teams can review and refine the proposed plan before generating a solution. ### Testing and operational review Validate solutions with synthetic test data or uploaded samples across expected scenarios, exceptions, and edge cases. Queues, outputs, activity logs, dashboards, and status reports help teams review runs and identify failures. ### Governance for agents across platforms Register and govern agents built with Azure AI Foundry, AWS Bedrock, Google Vertex AI, LangGraph, Google ADK, Microsoft Semantic Kernel, and Microsoft Agent Framework, without requiring teams to rebuild existing agents. ### Runtime controls and audit trails Apply policy gates and approvals within execution paths, record governed actions and exceptions, and use a kill switch to halt agent execution. Configured compensating actions may be triggered where supported. ## Use Cases ### Coordinate governance across agent platforms Organizations running agents on multiple frameworks can register them in a shared governance view, track ownership and permissions, and trace policies, approvals, and exceptions. ### Turn a business use case into a build plan Business and technical teams can capture a use case’s context and dependencies, then produce requirements and technical design materials to guide implementation. ### Validate an agentic solution before deployment Solution teams can review generated agent roles and workflows, test happy paths and edge cases with synthetic or sample data, and inspect run results before moving toward broader deployment. ### Control high-impact workflow execution Teams can define approval points, access boundaries, confidence thresholds, and exception handling for agent workflows that use enterprise data, tools, or systems. ## Frequently Asked Questions ### Can ZBrain govern agents that were built elsewhere? Yes. The platform can onboard agents built with Azure AI Foundry, AWS Bedrock, Google Vertex AI, LangGraph, Google ADK, Microsoft Semantic Kernel, and Microsoft Agent Framework into its governance layer. ### What materials can Solution Builder use? It can use ZBrain Design deliverables or uploaded materials such as BRDs, PRDs, process documents, architecture specifications, integration details, data schemas, sample files, and output templates. ### Can teams review a solution before it is generated? Yes. Solution Builder proposes agents, tools, workflows, and test data packages, and teams can review and refine the plan before solution generation. ### Where does ZBrain run? 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. ### How are the plans structured? The Growth plan is credit-based and includes a monthly credit allowance; the Enterprise plan is described as not requiring credits and includes custom SSO, unlimited builder users, unlimited integrations, deployment assistance, and API access. Enterprise pricing is arranged through a demo request. ## Quick Facts - **Product type**: Enterprise AI platform for agentic solution development and governance - **Governance scope**: Enterprise, functional, and application levels - **Deployment environment**: Client-selected cloud environment, tenant, and region - **Supported agent frameworks**: Azure AI Foundry, AWS Bedrock, Google Vertex AI, LangGraph, Google ADK, Microsoft Semantic Kernel, and Microsoft Agent Framework - **Plan structure**: Credit-based Growth plan and no-credit Enterprise plan - **Solution workflow**: Use-case analysis, technical design, solution build, validation, and runtime governance