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Understanding Google AI Ultra: What’s Behind the Premium AI Experience?

Google AI Ultra, a new premium subscription unveiled at Google I/O 2025, powers many of the above-mentioned innovations like Agent Mode and Veo 3. At $249.99 per month (50% off for the first three months for new users), it offers top-tier access to advanced AI models like Gemini 2.5 Pro with Deep Think mode, tools like Flow for 1080p video creation, and Whisk Animate for eight-second video clips. It also integrates Gemini into apps like Gmail and Chrome, plus 2TB of storage across Google Drive, Gmail, and Photos. Available only in the U.S. for now, with global expansion planned.

Gemini’s “Agent Mode”

Imagine having an AI executive assistant that doesn’t just chat but acts—booking your flights, researching topics, and managing your Google apps like a pro. Gemini’s new “Agent Mode” transforms it into a powerful executive assistant, capable of orchestrating complex, multi-step tasks with minimal oversight. It integrates advanced features like live web browsing, in-depth research, and smart connections with Google apps, allowing users to state objectives and let Gemini handle the execution. This feature is initially available for desktop users with the Google AI Ultra plan.

Veo 3 and Flow

Veo 3 can generate videos with audio—dialogue, sound effects, and music—all from a text prompt, while Flow lets users storyboard and edit within one platform. Together, they make video creation feel almost magical, raising questions about how far AI can take storytelling. These tools are accessible through the Gemini Ultra subscription, potentially marking the dawn of a new era for filmmakers and creators.

AI Mode in Search

Google’s AI Mode for Search, now rolling out to all U.S. users, enhances the search experience with advanced reasoning and multimodality. Features like Deep Search tackle complex queries by issuing hundreds of searches to create expert-level reports, while Search Live, powered by Project Astra, lets you interact with the world in real time using your camera—for example, pointing at a project to get instant explanations.

Imagen 4

Imagen 4, Google’s latest text-to-image model, pushes the boundaries of visual creativity with photorealistic outputs at up to 2K resolution. Faster than its predecessor, it excels at rendering fine details like fabrics and water droplets, powering tools like Flow for filmmaking and beyond. Available to Gemini Ultra subscribers, this model makes us wonder how AI-generated art might blur the lines between reality and imagination.

Developer Tools

Google I/O 2025 brought a suite of developer tools that could redefine how AI applications are built. Stitch, a new AI-powered tool, generates UI designs and frontend code from natural language or image prompts, with export options to CSS/HTML or Figma. Google AI Studio now integrates Gemini 2.5 Pro into its code editor for faster prototyping, while the Gemini API adds features like controllable text-to-speech for custom audio output, asynchronous function calling, and the Computer Use API for web browsing capabilities (available to trusted testers)

Businesses are rethinking how they deliver customer support, and many are turning to Google Contact Center AI (CCAI) to lead the charge. This powerful solution from Google Cloud is redefining contact center operations by embedding AI agents into every layer of the customer experience.

As a Google Cloud Partner focused on enabling digital transformation, we’re excited about how CCAI helps organizations deliver faster, smarter, and more scalable support.

What Is Google Contact Center AI?

Google Contact Center AI is a suite of artificial intelligence tools that enhance contact center performance. It combines conversational virtual agents, real-time support tools for human agents, and advanced analytics in one unified platform.

What sets CCAI apart is its use of generative AI, the same type of large language models behind leading chatbots, to understand customer intent, personalize interactions, and support agents with real-time recommendations.

How CCAI Creates Business Value

1. AI Agents That Understand and Assist
At the heart of Google CCAI are AI agents—virtual assistants that can manage calls and chats around the clock. Built on Dialogflow CX, these agents use natural language understanding to resolve routine issues and escalate complex cases to human reps when needed.

2. Real-Time Support for Human Agents
Using Google Cloud’s generative AI, CCAI equips live agents with contextual suggestions, auto-generated summaries, and sentiment analysis. This reduces handling time and boosts customer satisfaction by ensuring quick, consistent, and accurate responses.

3. Omnichannel and Multilingual Support
Whether your customers connect through phone, web, or messaging apps, Google CCAI ensures a seamless experience. With support for over 40 languages and native integration with leading CRMs and telephony systems, it’s ready for both local and global teams.

4. Built-In Analytics and Insights
Supervisors can use CCAI’s analytics to monitor customer sentiment, identify trends, and improve agent training. This level of insight helps contact centers continuously optimize their service delivery.

5. Scalable, Cloud-Native, and Easy to Integrate
As a fully managed service on Google Cloud, CCAI is scalable, secure, and easy to deploy across existing infrastructure. It works with most contact center platforms and integrates with enterprise workflows, making it ideal for businesses in the USA and Canada looking for rapid modernization.

Why Businesses Are Adopting CCAI

Customer expectations are evolving fast—and so must your support strategy. By leveraging Google Contact Center AI, businesses can improve resolution times, lower support costs, and deliver a consistent experience across every channel.

Whether you’re scaling up or reimagining your contact center, now is the time to explore what AI-driven service can do for your customers.

Victoria, BC – April 10, 2025 – Premier Cloud is proud to announce its selection as a launch partner for Google Agentspace, Google’s groundbreaking new AI platform designed to redefine enterprise search and productivity for organizations of all sizes.

With deep expertise in Google Cloud and artificial intelligence, Premier Cloud is uniquely positioned to help businesses harness the full potential of Agentspace. As part of this launch, Premier Cloud will work closely with customers to implement the platform and develop customized AI agents tailored to their operational goals. This builds on the company’s extensive experience in driving AI adoption across industries, including initiatives such as streamlining customer support systems to reduce response times, developing intelligent data retrieval solutions to improve knowledge management, and automating workflows to increase operational efficiency.

Google Agentspace introduces a new standard in enterprise AI, enabling seamless search across internal data sources with Google-quality intelligence. It combines advanced security, privacy, and compliance with a unified productivity platform that integrates with cutting-edge tools like Gemini, NotebookLM, Imagen, and Veo. This holistic approach simplifies complex workflows while ensuring that organizations remain agile, secure, and data-driven.

To learn more about Premier Cloud’s AI and ML offerings, including how Google Agentspace can transform an organization, visit premiercloud.com/ai-and-ml or request a one-hour Agentspace Use Case Discovery session by contacting us directly. 

One of the most exciting developments in the realm of Artificial Intelligence is AI agents—intelligent assistants that can automate tasks, provide insights, and enhance productivity. If you’re unfamiliar with AI agents and Google Agentspace, this guide will break it down for you.

What are AI Agents?

Google Agentspace is an enterprise AI platform that combines Google’s search technology, Gemini’s advanced reasoning, and enterprise data to create intelligent AI assistants. These AI-powered agents allow employees to interact with company knowledge using natural language and take action across applications.

Unlike large language models (LLMs) such as Gemini and ChatGPT, which focus on generating responses based on probabilistic predictions, AI agents go beyond just generating responses—they take actions, execute workflows, and integrate directly with enterprise systems. In other words, AI agents don’t just give suggestions—they actually perform tasks based on enterprise data and business applications.

What is Google Agentspace?

Google Agentspace is an enterprise AI platform that combines Google’s search technology, Gemini’s advanced reasoning, and enterprise data to create intelligent AI assistants. These AI-powered agents allow employees to interact with company knowledge using natural language and take action across applications.

🔹 Blended enterprise search – Find relevant information across internal and external sources
🔹 Automated workflows – AI agents handle research, content generation, and planning
🔹 Custom and pre-built AI agents – Employees can use Google’s expert AI agents or build their own

Key Features of Google Agentspace

1. Enterprise Search Across Multiple Platforms

Modern organizations use various tools for project management, collaboration, and content storage. Google Agentspace integrates with first- and third-party applications, including Google Drive, SharePoint, Jira, Salesforce, and more. It uses advanced search and AI reasoning to find relevant information across structured and unstructured data.

2. Multimodal AI

• 📄 Text – Understands and retrieves relevant information from documents, reports, and chat logs
• 🎨 Images – Allows users to upload images and ask questions about their content (e.g., extracting text from an invoice or analyzing a company logo)
• 🎙 Audio – Can summarize recorded meetings or provide podcast-like insights
• 🎥 Video – Extracts key insights from video content, making it easier to process large amounts of information

Google Agentspace goes beyond traditional text-based search by incorporating multimodal AI, meaning it can process, analyze, and generate insights across different types of data, including:

3. Pre-built and Custom Agents

In addition to multimodal AI, Google Agentspace provides a suite of pre-built AI agents designed to automate complex enterprise tasks. You can also create your own AI agents using low-code or no-code frameworks

Key Benefits of Pre-Built Agents:

🔹 Grounded in Enterprise Data – Unlike generic chatbots, these agents operate using real-time company data.
🔹 Task-Oriented – Instead of just providing information, they can perform actions in enterprise applications.
🔹 Integrated with Google & Third-Party Tools – Agents work across Google Workspace, Jira, Salesforce, ServiceNow, and other business platforms.

4. NotebookLM for Research and Data Synthesis

NotebookLM is a built-in tool within Google Agentspace that helps users summarize and extract insights from documents. Employees can upload PDFs, URLs, tests, and audio files, and the AI can:
✅ Generate structured summaries
✅ Provide citations for retrieved information
✅ Create interactive responses for deeper analysis

5. Security, Compliance, and Access Control

Google Agentspace is built with enterprise-grade security and compliance standards to ensure data privacy. Features include:

• Role-based access control (RBAC) – Ensures employees can only access relevant data
• Data encryption – Protects data both at rest and in transit
• Regulatory compliance – Meets standards like GDPR, HIPAA, and VPC Service Controls

How to Get Started with Google Agentspace?

Google Agentspace is available in multiple tiers, including:

• NotebookLM Plus Enterprise – Provides enhanced research tools with NotebookLM
• Google Agentspace Enterprise – Enables enterprise search and multimodal AI interactions
• Google Agentspace Enterprise Plus – Adds advanced AI automation, research agents, and action execution

Interested in learning more and onboarding to Google Agentspace? Contact Premier Cloud today to learn more about Google Agentspace and how AI agents can transform your enterprise productivity.

VICTORIA, BC. February 12, 2025 — Premier Cloud is proud to be named in CRN’s 2025 Managed Service Provider (MSP) 500 list in the Pioneer 250 category. This recognition highlights our continued commitment to delivering secure, scalable cloud and IT solutions that enhance efficiency and drive business success.

CRN’s MSP 500 list identifies top North American managed service providers that lead innovation in IT. The Pioneer 250 category acknowledges MSPs that support small and mid-sized businesses with cutting-edge technology solutions that help them navigate evolving IT challenges and stay competitive.

Premier Cloud specializes in Google Cloud and AI-driven solutions, helping businesses streamline IT operations, enhance security, and maximize technology investments. By offering proactive support, managed cloud services, and AI-powered automation, we ensure businesses can optimize performance while focusing on growth.

Premier Cloud’s client-centric approach is at the heart of our growth strategy, ensuring we consistently meet and exceed our clients’ expectations with each interaction. We are eager to continue expanding and evolving while strengthening our connections with clients and partners. Our dedication to delivering exceptional solutions that drive business growth and innovation remains unwavering.

See the full list here: https://www.crn.com/rankings-and-lists/msp2025

For more information, please contact: 
Alex Shahbazfar
alex.s@premiercloud.com 
888-866-2230

1. Introduction

Real-world applications often require access to dynamic and constantly changing information. This tutorial focuses on integrating external data sources, specifically APIs, into Vertex AI Agent Builder, unlocking possibilities for truly intelligent conversational experiences. By doing so, your agents can access real-time information, stay relevant, and provide accurate responses.

2. Understanding the Basics

What is Vertex AI Agent Builder?

Vertex AI Agent Builder is a platform for creating AI agents capable of interacting with and understanding the world. It supports natural language queries, integrates enterprise data, and becomes even more powerful with external data sources like APIs.

Static vs. Dynamic Data

Static data, such as PDFs or CSV files, quickly becomes outdated, limiting its use. For example, an e-commerce support agent relying on static data can’t provide live updates on product availability or shipping timelines. Dynamic sources, like APIs, offer real-time information, enabling agents to respond effectively to evolving needs.

3. Preparing for Integration

API Setup

To illustrate dynamic data integration, we use a Warehouse Address API. This API retrieves a warehouse’s address based on its ID, offering real-time updates. It is implemented using Flask and deployed on Cloud Run.

The configuration is defined in a YAML file, which acts as a blueprint for the API. It includes details like API paths, request parameters, and response formats. You can check the YAML file given below:

openapi: 3.0.0
info:
 title: Warehouse Address API
 version: v1
servers:
 - url: 'https://my-warehouse-api-zycua53bta-uc.a.run.app'
paths:
 /warehouses/{warehouseId}/address:
   get:
     summary: Get Warehouse Address
     description: Retrieves the address of a warehouse by its ID.
     parameters:
       - in: path
         name: warehouseId
         schema:
           type: integer
           format: int64
         required: true
         description: The ID of the warehouse.
     responses:
       '200':f
         description: Successful response with the warehouse address.
         content:
           application/json:
             schema:
               type: string
               description: The full address of the warehouse.
       '404':
         description: Warehouse not found.

This YAML file is crucial for integrating the API with Vertex AI Agent Builder.

Connecting Your API

1. Open the Agent Builder console.
2. Navigate to Tools and create a new tool.
3. Enter the tool’s name, type (OPENAPI), and description.
4. Paste the YAML file content and save it.
5. Proceed to create your agent.

4. Building and Testing Your Agent

Agent Setup

1. Create a new agent in Vertex AI.
2. Define its name, goal, and step-by-step instructions.
3. Reference the tool created earlier using the format: ${TOOL: Tool_name}.

Test your Agent

Just like any software, agents need thorough testing. This helps identify bugs in their code, understand their current capabilities, and most important, simulate real interactions with users to refine the overall customer experience. 

While you are in the console, go ahead and select the appropriate agent and select the generative model of your choice and you now ask questions to the agent and the response will be coming from the API.

5. Publishing the Chat App

Now that the Chat App is up and running, it’s time to publish it and embed it into our website. To publish your Chat App, click on the Publish button which will prompt you with the following:

You have to specify the agent environment, followed by the Access type and the UI Style that you want. Once you have all of this set, go ahead and click on Enable the unauthenticated API.

6. Conclusion

This tutorial demonstrated how to integrate external data sources into Vertex AI Agent Builder, using APIs to create dynamic conversational agents. By following these steps, you can build intelligent chat applications that adapt to real-time data and deliver superior user experiences.

By Aryan Irani

We are thrilled to announce that Ryan Brady, Premier Cloud’s VP of Sales, has been recognized as one of CRN’s Next-Gen Solution Provider Leaders for 2024! 

This prestigious honor spotlights young professionals under 40 already making a significant impact within the IT channel. Ryan’s drive, vision, and dedication to innovation have played an instrumental role in shaping Premier Cloud’s strategic direction and elevating our position in the marketplace.

Key Accomplishments That Set Us Apart

Over the past year, Ryan has led numerous initiatives that have dramatically diversified Premier Cloud’s product and service portfolio, creating multiple new revenue streams. We are proud to be a top seller in North America for sales of Google’s new Gemini product. This is a testament to our ability to stay ahead of industry trends and meet market demands for cutting-edge AI solutions.

Under Ryan’s leadership, we’ve also attained Premier status within the Google Cloud Partner Program and received several Specialization awards for our expertise in delivering Google Workspace and Google Cloud services. These accomplishments not only validate the exceptional quality of our solutions but also highlight our team’s dedication to excellence in every client engagement.

The Role of AI in Our Growth Journey

Artificial intelligence is transforming every industry, and Premier Cloud is at the forefront of this shift. As a reseller of AI solutions, particularly Google’s Gemini for Google Workspace and Vertex AI, we are uniquely positioned to help companies explore, understand, and implement AI meaningfully. Ryan’s vision for AI has enabled us to become trusted advisors in this space, helping clients bring their AI aspirations to life.

Join Us in Celebrating This Milestone

Ryan Brady’s inclusion in CRN’s Next-Gen Solution Provider Leaders list is a significant achievement, not just for him but for everyone at Premier Cloud. It’s a testament to the hard work, dedication, and innovative thinking that defines our team and drives our success. 

We look forward to building on this momentum as we transform the IT channel, empower our clients, and push the boundaries of what’s possible.

By Aryan Irani

As AI continues to evolve, Google’s Gemini AI models, developed by DeepMind, have made it easier for everyone—from individuals to businesses—to benefit from powerful AI tools. Whether you’re looking to speed up simple tasks or take on complex projects, there’s a Gemini model suited to your needs. In this guide, we’ll walk you through the key Gemini models and help you decide which one is right for you.

Meet the Gemini Family

The Gemini models are designed to handle various tasks, from quick, real-time responses to more complex, data-heavy applications. Below, we’ve outlined three of the main models—Gemini 1.5 Flash, Flash-8B, and Pro—so you can quickly see which one fits your requirements.

Quick Comparison of Gemini Models

We’ve made it easy to compare the key features of each model in the table below. Whether you’re after speed, complexity, or enterprise-level performance, this table helps you pick the right option.

What Are Tokens and Why Do They Matter?

Tokens represent pieces of the input or output text that the model processes. Think of tokens as chunks of words, parts of a sentence, or data points. A higher number of tokens means the model can handle longer and more complex tasks, while fewer tokens suit quicker, simpler tasks. For example, if you need to work with large data sets or generate long, detailed outputs, a model with a higher token count—like Gemini 1.5 Pro—would be ideal. On the other hand, for faster, real-time responses in customer service, a lower token count in Gemini 1.5 Flash would work perfectly.

What’s Important to Know About Each Model?

Gemini 1.5 Flash

This model is all about speed. It’s great for tasks that need quick responses, like customer service chatbots or real-time data analysis. Think of it as a fast, reliable worker who delivers results without much delay. If you’re dealing with simple tasks that need to be done right away, this model is a great fit.

Gemini 1.5 Flash-8B

This is the more advanced version of the Flash model. It’s still fast, but with 8 billion parameters, it can handle more complex tasks. If your work involves multitasking or analyzing both text and images at the same time (like in voice assistants or image recognition), this model provides a good balance of speed and complexity.

Gemini 1.5 Pro

For big, enterprise-level tasks, the Pro model is your go-to. It’s designed for companies that need high performance and detailed, accurate responses. Whether you’re working with large datasets, analyzing healthcare information, or generating financial reports, this model offers the power and accuracy needed for critical tasks.

A Glimpse Into Google AI Studio

Google AI Studio is a platform designed to make it easy for you to experiment with these Gemini models. It’s like a testing ground where you can quickly try out different AI models by entering prompts and seeing how the models respond. The interface lets you choose from different models, view the token count, and adjust advanced settings before running your prompts. Once you find something that works, you can even export the code and integrate it into your applications. It’s a great way to see how the different Gemini models perform, helping you pick the right one for your project.

How to Choose the Right Model

When choosing the best Gemini AI model, it really comes down to what you need it to do. Here’s a quick guide to help you decide:

• Need something fast for simpler tasks? Go for Gemini 1.5 Flash. It’s fast and effective for everyday tasks that require quick, real-time responses.
• Want speed but need to handle more complexity? The Gemini 1.5 Flash-8B gives you the speed of Flash with the ability to process more complicated inputs, making it great for advanced chatbots or apps that involve both text and images.
• Working with large-scale, high-accuracy projects? Choose the Gemini 1.5 Pro. This model is perfect for enterprises, handling big data, financial analysis, or in-depth healthcare tasks with ease.

Making the Most of Gemini AI Models

Now that you know the basics, using Gemini AI models is easy. You can experiment with them on platforms like Google AI Studio to get a feel for how they work and see which one suits your needs best. Whether you’re automating customer support, building an AI assistant, or diving into detailed data analysis, there’s a Gemini model ready to help.