
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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Sendbird provides AI-powered omnichannel communication solutions, including AI agent for customer service, Chat API, and Business Messaging for seamless customer conversations across mobile apps, websites, social media, and more. Our platform supports iOS, Android, JavaScript, Unity, and .NET.
Sendbird’s AI Agent Platform enables businesses to automate customer support across a wide range of channels, including SMS, web, mobile apps, and social media. This solution leverages AI to provide proactive, continuous support by anticipating customer needs and engaging them on their preferred platforms. Businesses can build and manage their own AI agents with an easy-to-use interface, ensuring smooth customer interactions. The platform integrates seamlessly with existing systems, providing businesses with insights into customer conversations, improving agent performance, and offering reliable support in high-traffic environments.
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Origon
Origon serves as a comprehensive platform for developing and managing full-stack AI agents, designed as a cohesive "Agentic Operating System" that facilitates every phase of autonomous AI systems, from initial design through deployment and monitoring. It features a user-friendly Studio that allows for visual agent creation via drag-and-drop functionality, alongside Sessions that enable real-time observation, behavior tracking, and debugging, while Insights dashboards provide centralized performance analytics, reliability monitoring, and outcome evaluation. Operating natively on specialized infrastructure tailored for optimal low-latency performance and enhanced security, Origon eliminates reliance on external cloud APIs and includes an integrated knowledge engine that links agents to contextual memory and domain-specific data, ensuring that their responses remain grounded and coherent. The platform supports a wide array of connectors and APIs, such as chat, voice, WhatsApp, SMS, email, and telephony, empowering agents to execute code and interact seamlessly with real-world systems at the click of a button. Additionally, the versatility of Origon allows businesses to customize their AI agents further, catering to specific operational needs and enhancing overall efficiency.
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Calljmp
Calljmp is a developer-first AI runtime for building and running long-lived, stateful agent workflows in production.
Unlike AI agent frameworks that focus mainly on authoring logic in code, Calljmp provides a managed runtime that handles execution concerns by default. This includes durable state persistence, pause and resume for human-in-the-loop workflows, safe retries with idempotency, and built-in observability across every step of an agent’s execution.
Calljmp is designed for teams using TypeScript who want to ship production-grade AI systems without stitching together queues, databases, custom state machines, and monitoring infrastructure. Developers write agent workflows as code, while the runtime guarantees reliable execution over time, even across crashes, restarts, and long waits.
Calljmp targets the gap between developer-first agent frameworks and heavy workflow engines, offering a practical path from prototype to production for real-world AI agents.
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