
Gemini Enterprise Agent Platform is Google Cloud’s next-generation system for designing and managing advanced AI agents across the enterprise. Built as the successor to Vertex AI, it unifies model selection, development, and deployment into a single scalable environment. The platform supports a vast ecosystem of over 200 AI models, including Google’s latest Gemini innovations and popular third-party models. It offers flexible development tools like Agent Studio for visual workflows and the Agent Development Kit for deeper customization. Businesses can deploy agents that operate continuously, maintain long-term memory, and handle multi-step processes with high efficiency. Security and governance are central, with features such as agent identity verification, centralized registries, and controlled access through gateways. The platform also enables seamless integration with enterprise systems, allowing agents to interact with data, applications, and workflows securely. Advanced monitoring tools provide real-time insights into agent behavior and performance. Optimization features help refine agent logic and improve accuracy over time. By combining automation, intelligence, and governance, the platform helps organizations transition to autonomous, AI-driven operations. It ultimately supports faster innovation while maintaining enterprise-grade reliability and control.
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Assembled combines AI agents with advanced workforce management to give support teams the speed, flexibility, and control they need to excel. Our platform streamlines staffing for both in-house and outsourced teams, delivers forecasts with over 90% accuracy, and automates more than half of customer conversations. Whether it’s chat, email, or voice, Assembled orchestrates every interaction, allocating work between AI and human agents in real time. Leading brands like Stripe, Canva, and Robinhood rely on Assembled to boost performance and turn support into a growth driver. Key capabilities include scheduling, forecasting, live performance monitoring, vendor management, AI-powered chat, voice, and email agents, plus an AI Copilot that provides instant guidance, suggested responses, and rapid action tools for agents.
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Claude Cowork
Claude Cowork is an AI-powered productivity platform that autonomously handles knowledge work tasks across local files, applications, and business documents. Built for non-technical users, the platform allows professionals to delegate complex workflows such as document preparation, research synthesis, data extraction, and file organization without needing technical expertise or manual prompt engineering. Claude Cowork navigates multiple information sources, processes large volumes of content, and delivers structured outputs while maintaining human oversight for important decisions. Its desktop-based approach enables seamless interaction with the tools and files employees already use, helping organizations improve efficiency, reduce administrative workloads, and accelerate decision-making.
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IronClaw
IronClaw is an open-source runtime that prioritizes security, designed specifically for the execution of autonomous AI agents while incorporating robust protections for sensitive credentials and system access. This platform serves as a security-centric alternative to OpenClaw, functioning within encrypted enclaves on the NEAR AI Cloud or locally to safeguard sensitive information during its operation. Users can effortlessly launch AI agents via a one-click setup, ensuring that API keys, tokens, and passwords are securely stored in an encrypted vault, inaccessible to the AI itself. IronClaw takes security further by isolating each tool within its own WebAssembly sandbox, employing capability-based permissions and enforcing strict resource limitations to ensure that any compromised functionalities do not jeopardize the overall system. Constructed in Rust, it upholds memory safety at compile time, successfully mitigating common vulnerabilities like buffer overflows and use-after-free errors. With these features, IronClaw not only enhances the security of AI deployments but also instills confidence in users regarding the integrity of their sensitive data throughout the execution process.
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