Gemini Enterprise Agent Platform is an advanced AI infrastructure from Google Cloud that enables organizations to build and manage intelligent agents at scale. As the evolution of Vertex AI, it consolidates model development, agent creation, and deployment into a unified platform. The system provides access to a diverse library of over 200 AI models, including cutting-edge Gemini models and leading third-party solutions. It supports both low-code and full-code development, giving teams flexibility in how they design and deploy agents. With capabilities like Agent Runtime, organizations can run high-performance agents that handle long-duration tasks and complex workflows. The Memory Bank feature allows agents to retain long-term context, improving personalization and decision-making. Security is a core focus, with tools like Agent Identity, Registry, and Gateway ensuring compliance, traceability, and controlled access. The platform also integrates seamlessly with enterprise systems, enabling agents to connect with data sources, applications, and operational tools. Real-time monitoring and observability features provide visibility into agent reasoning and execution. Simulation and evaluation tools allow teams to test and refine agents before and after deployment. Automated optimization further enhances agent performance by identifying issues and suggesting improvements. The platform supports multi-agent orchestration, enabling agents to collaborate and complete complex tasks efficiently. Overall, it transforms AI from a productivity tool into a fully autonomous operational capability for modern enterprises.
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BAND develops comprehensive interaction frameworks tailored for large-scale applications of distributed AI agents. This platform enables real-time, collaborative communication between agents and humans while integrating a runtime control plane that maintains policy adherence, establishes authority boundaries, and guarantees transparency across varied systems.
Moreover, BAND supports developers, engineering teams, and leaders overseeing enterprise platforms that manage multi-agent ecosystems across internal frameworks, SaaS offerings, and collaborative environments with partners. This robust support not only improves operational efficiency but also stimulates innovation within intricate organizational frameworks, ultimately driving progress and adaptability in a rapidly evolving technological landscape.
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Maetra
Maetra acts as a specialized governance control plane designed for teams overseeing AI agents that utilize various tools. It identifies these agents along with their corresponding repositories, evaluates risks through predefined frameworks, and checks possible actions against versioned governance policies before they are carried out. Furthermore, it streamlines the process for human approvals, scrutinizes prompts and tool interactions for vulnerabilities during runtime, guarantees that ongoing tasks stay in line with authorized goals, and preserves immutable records of decisions for auditing. The system consists of multiple modules, including Govern, Secure, Task Guard, Interaction Guard, Discover, Comply, Audit, and Decision Intelligence, which can operate autonomously or collaboratively as a unified control plane, thus improving operational effectiveness and regulatory compliance. This multifaceted approach ultimately fosters a robust framework for managing and overseeing the actions of AI agents within organizations, ensuring that they function within the established guidelines. By promoting accountability and transparency, Maetra strengthens the governance of AI technologies in a rapidly evolving landscape.
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Enkrypt AI
Enkrypt AI is an agentic AI security and compliance platform that helps enterprises identify, mitigate, monitor, and govern risks associated with AI models, applications, agents, and supporting infrastructure. The platform is designed to cover AI security threats and compliance requirements across different models and modalities while allowing organizations to continuously evaluate AI systems as they evolve. Its dynamic red teaming capabilities generate use-case-specific attacks that adapt in real time to uncover security, safety, compliance, and brand risks beyond those identified through static testing. Enkrypt AI can test for threats including prompt injection, jailbreaking, data leakage, model inversion, adversarial attacks, drip attacks, unsafe actuation, policy violations, and misuse by end users. It also evaluates AI quality and safety risks such as hallucinations, model drift, bias and discrimination, toxic content, deceptive behavior, misleading outputs, lack of explainability, and brand misalignment. Real-time guardrails detect and stop risky interactions as they occur while adapting to new prompts, behaviors, and emerging threats. Continuous monitoring gives security and compliance teams visibility into AI risks, protection effectiveness, and areas requiring action as models and applications change. Enkrypt AI's compliance functionality converts internal policies and external regulatory requirements into automated guardrails and generates evidence that can support audits and compliance programs. The product portfolio includes Agent Red Teaming, Agent Guardrails, an Agent Policy Engine, AI Data Risk Audit, MCP Scanner, and MCP Gateway for protecting AI agents, their data, and their connections to tools and infrastructure. Enkrypt AI supports use cases including customer-facing AI agents, frontier models, AI compliance and auditing, third-party AI risk, secure AI development, data risk assessment, and MCP security.
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