
Customer experience shouldn't run on disconnected tools and static scripts. Dialpad Contact Center brings voice, digital channels, and human agents together in a single AI-native platform, built to act — not just record — on every customer interaction.
This is Agentic AI in practice: agents that reason through a problem, take the next step, and drive it to resolution without waiting on a human to intervene. Where legacy systems leave data trapped in silos, Dialpad Contact Center closes that gap, linking voice and data so context travels with the customer instead of getting lost between systems.
The payoff compounds. Dialpad has already generated over 775 million AI recaps, and each new interaction adds to a growing base of operational intelligence — sharper resolution paths, more productive agents, better outcomes quarter over quarter. None of it runs unchecked: Dialpad's Guardian layer keeps AI operations secure and governed, so intelligence scales without sacrificing oversight.
In practice, that means up to 80% of issues get resolved autonomously, freeing your team to focus on the conversations that genuinely need a human. Intelligence works at the edge; people stay at the center of the experience.
And you don't have to take the ROI on faith. Through Dialpad's Proving Ground, enterprises can validate performance and cost savings before rolling out at scale — a far more reliable path than betting on a brittle, rules-based bot.
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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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Holo2
The Holo2 model family from H Company offers a blend of affordability and high performance in vision-language models specifically designed for computer-based agents that can navigate, localize user interface elements, and function across web, desktop, and mobile platforms. This new series, which is available in sizes of 4 billion, 8 billion, and 30 billion parameters, builds upon the foundations laid by the earlier Holo1 and Holo1.5 models, ensuring strong grounding in user interfaces while making substantial improvements to navigation abilities. Utilizing a mixture-of-experts (MoE) architecture, the Holo2 models activate only the necessary parameters to maximize operational efficiency. These models have been trained on carefully curated datasets focused on localization and agent functionality, allowing them to seamlessly replace their predecessors. They provide support for effortless inference in environments compatible with Qwen3-VL models and can be easily incorporated into agentic workflows such as Surfer 2. In benchmark evaluations, the Holo2-30B-A3B model demonstrated impressive results, achieving 66.1% accuracy on the ScreenSpot-Pro test and 76.1% on the OSWorld-G benchmark, thereby establishing itself as the leader in the UI localization sector. Additionally, the advancements in the Holo2 models make them a compelling choice for developers looking to enhance the efficiency and performance of their applications.
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Lux
Lux introduces a breakthrough approach to AI by enabling models to control computers the same way humans do, interacting with interfaces visually and functionally rather than through traditional API calls. Through its three distinct modes—Tasker for procedural workflows, Actor for ultra-fast execution, and Thinker for complex problem-solving—developers can tailor how agents behave in different environments. Lux demonstrates its power through practical examples such as autonomous Amazon product scraping, automated software QA using Nuclear, and rapid financial data retrieval from Nasdaq. The platform is designed so developers can spin up real computer-use agents within minutes, supported by robust SDKs and pre-built templates. Its flexible architecture allows agents to understand ambiguous goals, strategize over long timelines, and complete multi-step tasks without manual intervention. This shift expands AI’s capabilities beyond reasoning into hands-on action, enabling automation across any digital interface. What was once a capability reserved for large tech labs is now accessible to any developer or team. Lux ultimately transforms AI from a passive assistant into an active operator capable of working directly inside software.
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