Google Agentspace: Building Custom AI Agents for Enterprise Search

Google Agentspace has become a revolutionary force in enterprise AI adoption, with major companies like Wells Fargo, KPMG, and Banco BV leading the way. The platform combines powerful AI agents, enterprise search capabilities, and company data into one solution that runs on Gemini's advanced reasoning capabilities.

Companies of all sizes now utilize Agentspace to boost employee productivity through its no-code Agent Designer. Teams can create custom AI agents regardless of their technical expertise. The platform provides solutions for sales, marketing, HR, and software development teams. Pricing begins at $9 monthly per user for NotebookLM for Enterprise and goes up to $45 for the Enterprise Plus tier with additional features.

This piece will show you how Google Agentspace works. You'll learn about its core features and practical strategies to discover the full potential of AI transformation for your organization.

What is Google Agentspace: Core Components and Architecture

Google Agentspace marks a major step forward in enterprise AI technology. It combines Gemini's reasoning capabilities with Google-quality search and enterprise data access. The platform connects employees with AI agents smoothly, whatever the location of company data.

Gemini-powered AI foundation for enterprise search

Google Agentspace builds on Gemini, Google's advanced AI model that gives the platform its intelligence and reasoning abilities. This combination helps Agentspace provide conversational support, tackle complex questions, suggest solutions, and take action based on each company's information.

The platform turns scattered enterprise content into practical knowledge. It builds a complete enterprise knowledge graph for each customer that links employees to their teams, documents, software, and available data. This smart connection system understands context in ways that are nowhere near what traditional keyword search can do.

Google Agentspace works through three main tiers:

• NotebookLM Enterprise: The foundation layer that enables complex information synthesis
• Agentspace Enterprise: The core search and discovery layer across enterprise data
• Agentspace Enterprise Plus: The advanced layer for custom AI agent deployment

Each tier adds to the previous one and creates an ecosystem where information flows naturally. The platform's security runs on Google Cloud's secure-by-design infrastructure. It has role-based access control (RBAC), VPC Service Controls, and IAM integration to protect data and ensure compliance.

NotebookLM Plus integration for document synthesis

NotebookLM Plus is a vital part of the Agentspace architecture that offers advanced document analysis and synthesis tools. Google started with NotebookLM as a personal research and writing tool. Now they've expanded its features for business use through NotebookLM Plus and Enterprise editions.

NotebookLM Enterprise lets employees upload information for synthesis, find insights, and work with data in new ways. Users can create podcast-like audio summaries from complex documents. The system supports more file types than the consumer version, including DOCX and PPTX. Users also get higher limits for notebooks, sources, and queries.

NotebookLM Enterprise runs in the customer's Google Cloud environment. This setup keeps all data within the customer's Google Cloud project and prevents external sharing. System administrators can manage it through the Google Cloud console. Users access notebooks through project-specific URLs and use preset IAM roles for access control.

Google has started rolling out an experimental version of Gemini 2.0 Flash in NotebookLM. This update will likely make the system faster and more capable within the Agentspace ecosystem.

Multimodal search capabilities across enterprise data

Google Agentspace stands out because of its multimodal search features that work with many types of data and storage systems. The platform understands text, images, charts, infographics, video, and audio. It finds relevant information in any format or storage location.

The multimodal search feature provides one company-branded search agent that acts as a central source of truth. It runs on Google's search technology and uses AI to understand what users want and find the most relevant information. The system works with both unstructured data like documents and emails, and structured data in tables.

The architecture has ready-made connectors for popular third-party apps that work smoothly with:

• Confluence
• Google Drive
• Jira
• Microsoft SharePoint
• ServiceNow
• Salesforce
• And more

This connection system helps employees access and search relevant data sources without switching apps. Agentspace works as a smart layer on top of existing enterprise systems instead of replacing them.

A recent upgrade integrates Agentspace's unified enterprise search directly into the Chrome search bar. Employees can now use the platform's search, analysis, and synthesis features without leaving their main work environment.

This well-designed architecture makes Google Agentspace a complete package. It combines Gemini's AI capabilities with enterprise data access and specialized agent features in a secure, adaptable framework built for business needs.

Building Custom AI Agents with No-Code Agent Designer

The game-changing feature of Google Agentspace makes it easier to create AI agents. The new no-code Agent Designer helps employees with any technical skill level build customized AI assistants. They can do this without writing code.

Step-by-step agent creation process

Anyone can learn to create a custom AI agent in Google Agentspace through a simple process. The first step opens the Agent Designer within the Agentspace platform. You then describe what you want your agent to do. The system takes this natural language input and sets up the agent's main functions and capabilities.

The next crucial step lets you choose which data sources your agent should access. This choice determines what information your agent can find and use during interactions. You then define specific actions your agent can perform, like searching documents, creating summaries, or linking to other enterprise systems.

Google offers the Vertex AI Agent Development Kit as another option for advanced users. This developer-focused tool has a growing library of connectors, triggers, and access controls. Developers can build complex agents and publish them directly to Agentspace.

Template selection and customization options

Google Agentspace offers various templates as starting points for different use cases. These templates help different departments:

• Business analysts create agents that find industry trends and generate data-driven presentations
• HR teams build agents that streamline employee onboarding
• Software engineers develop agents that spot and fix bugs proactively
• Marketing teams make agents for performance analysis and campaign optimization

The platform goes beyond basic templates. The Agent Designer's easy-to-use interface lets users adjust how agents work with enterprise data sources. You can customize how search results appear, add summaries, and create follow-up prompts.

Testing and refining agent performance

Testing becomes crucial before deployment once you set up your agent. The Agent Designer has built-in testing tools that let you simulate user interactions. This ensures your agent responds well to different inputs.

Key testing areas include:

1. Accuracy of information retrieval
2. Relevance of responses
3. Proper connection to data sources
4. Appropriate action execution

The platform lets you make conversational adjustments when issues arise. You can guide the agent to improve itself based on feedback. This continuous improvement process helps your agent get better through ground usage and feedback.

Deployment strategies for enterprise-wide adoption

The next challenge comes after you perfect your custom agent - rolling it out across your organization. Google Agentspace solves this with the Agent Gallery. This central hub helps employees discover all available agents in your enterprise.

The Agent Gallery works with an allowlist and shows employees agents from multiple sources:

• Custom agents built by internal teams
• Google's pre-built agents
• Partner-developed agents
• Agents from external platforms

This united approach breaks down traditional enterprise tool barriers. The platform stands out by working with agents from external platforms like Salesforce Agentforce and Microsoft Copilot. This creates a seamless experience.

Smart deployment targets specific teams that benefit most from particular agents. Linking agents to relevant team data sources keeps adoption rates high. Employees see immediate value from AI assistance that fits their context.

The Agent Designer transforms how enterprises implement AI. It moves from developer-focused to user-focused creation while keeping options open for complex technical solutions when needed.

Enterprise Search Implementation with Google Agentspace

Setting up Google Agentspace needs proper planning and setup to maximize its potential. Traditional search systems only work with keywords. However, Agentspace understands and searches across text, images, charts, videos, and audio files.

Setting up company-branded search experiences

You need to create a company-branded search experience as your organization's central source of truth. Start by opening your Google Cloud console and search for "agent builder." The API needs to be enabled if you're using it for the first time. Next, click "apps" from the left panel and select "create a new app." Choose the "enterprise search and assistant" option which is in preview mode.

This setup creates a search agent customized to your company's brand identity. Your employees can access this unified search through a web link. They can ask questions, see search suggestions, and create documents from one interface. Google has integrated Agentspace's search features directly into Chrome Enterprise. This allows employees to use these capabilities from their browser's search box.

Configuring data source connections

Google Agentspace Enterprise's strength comes from connecting to different data sources. Here's how to set up these connections:

1. Click on "data sources" from the left panel in the Google Cloud console
2. Select "create data store" and choose from available connectors
3. Configure authentication for your selected data source
4. Define synchronization settings (one-time or periodic)

Agentspace has ready-made connectors for many applications including:

• Document management: Google Drive, Box, Microsoft SharePoint
• Collaboration tools: Slack, Confluence, Teams
• Project management: Jira Cloud
• Customer data: Salesforce
• IT service management: ServiceNow

Managing access controls is vital during configuration. Agentspace follows the source application's access control lists (ACLs). This means indexed data keeps the original system's permissions. Your employees will only see results for content they can access. You won't need to create custom permission rules.

Implementing RAG for improved search accuracy

Retrieval Augmented Generation (RAG) makes Google Agentspace's search more accurate. Enable document chunking when you create your search data store to implement RAG well. This breaks documents into smaller, meaningful parts during ingestion. The result is better relevance and less work for language models.

The layout parser in your document processing settings should be configured for the best RAG setup. This parser spots document elements like headings, lists, and tables. It enables content-aware chunking that keeps meaning intact. You can choose which file types should use layout parsing. This works great for HTML, PDF, or DOCX files with complex structures.

Agentspace gives you three parsing choices: digital parser for machine-readable text, OCR parsing for scanned PDFs, and layout parser for structured documents. The layout parser stands out because it recognizes content elements and structure hierarchy. This improves both search relevance and answer quality.

Search analytics and continuous improvement

Google Agentspace provides powerful analytics tools in the Google Cloud console after implementation. These tools help you learn about search performance, query patterns, and how users interact with the system. Administrators can spot areas that need improvement.

Users can rate search results and generated answers in real-time. This feedback helps the system get better based on actual use. You can also see analytics by query types, data sources, and user groups to find specific areas to improve.

Look at search analytics often to find common queries with low satisfaction rates. Check which data sources users access most and keep them properly synced. You can adjust boosting and burying rules to improve how content appears in search results based on relevance.

These implementation steps help organizations build a powerful enterprise search system. It keeps getting better while maintaining strict access controls and data security.

Integrating Google Agentspace with Enterprise Systems

Uninterrupted connection between Google Agentspace and enterprise infrastructure creates real business value. The platform turns scattered data into applicable information by connecting information silos through powerful integrations without disrupting existing workflows.

Connecting to Google Workspace applications

Google Agentspace integrates deeply with Google Workspace applications to create a unified ecosystem where information moves freely between tools. The Workspace integration lets Agentspace draft Gmail responses, provide email thread summaries, and schedule meetings by checking Google Calendar availability automatically.

Google Drive integration significantly improves document management. Employees can search their organization's entire document library instantly after connecting Agentspace to Drive. The system maintains existing sharing permissions, so users see only the documents they have authorization to access.

The true value of these integrations shows when multiple Workspace applications work together. An employee asking about quarterly sales projections gets data from Drive spreadsheets, relevant Calendar events, and Gmail conversation context—all in one response.

Third-party integrations with Salesforce, Microsoft, and more

Agentspace connects to many third-party applications through dedicated connectors, which eliminates switching between different systems. Document management expands to Box and Microsoft SharePoint, where teams can search, create reports, and get AI-powered summaries of long documents.

Microsoft users get complete integration with:

• Outlook email and calendar for communication management
• SharePoint Online for document access and search
• Teams for collaboration content

Salesforce integration helps sales and customer service teams manage leads, update CRM records, and discover AI-powered sales insights. IT and engineering teams can utilize Jira, Confluence, GitHub, and ServiceNow connections to track tickets and manage documentation better.

Agentspace excels by incorporating agents built on external platforms. Teams can upload, access, and deploy Salesforce Agentforce or Microsoft Copilot agents directly in their Agentspace environment—this shows Google's dedication to interoperability.

API connectivity options for custom applications

Agentspace offers flexible API connectivity options for organizations with special needs. The platform connects to Dialogflow agents to create custom conversational experiences beyond standard features. These agents work as deterministic, fully generative, or hybrid solutions and connect to any service.

Custom agent connections help enterprises build sophisticated workflows for specific business tasks. A financial institution could create agents that handle fraud disputes, process refunds, manage lost credit cards, or update user records while maintaining security controls.

Google added support for the open Agent2Agent (A2A) Protocol. This breakthrough lets developers pick their preferred tools and frameworks while staying compatible with the broader Agentspace environment.

Agentspace maintains strict security protocols across all integration options. The platform follows source application access controls, manages role-based access, and guarantees data residency—keeping sensitive information safe as it moves between systems.

Real-World Applications Across Business Departments

Companies that use Google Agentspace see clear benefits in their departments. Their teams make better decisions and get more work done.

Marketing team use cases and ROI metrics

Marketing teams use Google Agentspace to create content that matches their brand voice. They also get evidence-based insights about their campaigns. Teams can now create individual-specific messages, product suggestions, and deals based on customer information. At Accenture, AI agents have made a major retailer's customer support better by adding self-service options that improve customer experience. Some other ways teams use it:

• Creating quality blogs and social posts that match brand tone
• Making audio summaries to speed up market research
• Finding content gaps through AI analysis of feedback

Capgemini has built AI agents with Google Cloud. These agents help retailers take orders through new channels and speed up their order-to-cash process.

HR department implementation examples

HR teams have simplified their administrative work with custom Agentspace agents. These agents answer employee questions about benefits, pay, and HR rules. This lets HR staff focus on more important work. AI helps match the right talent to specific projects.

HR departments use Agentspace in several ways. They help new employees settle in, create surveys to find areas of improvement, and give staff easy access to company policies. Wagestream, a financial wellbeing platform, handles over 80% of internal customer inquiries with Gemini models.

IT and development team efficiency gains

Software teams use Google Agentspace to find and fix bugs faster, which speeds up product releases. Developers check code quality, find existing solutions, and spot potential problems early.

Cognizant created an AI agent with Vertex AI and Gemini that helps legal teams write contracts. It assigns risk scores and suggests ways to improve operations. Multimodal, part of Google for Startups Cloud AI Accelerator, uses AI agents to handle complex financial tasks. These agents process documents, search databases, and create reports.

Finance and legal compliance applications

Google Agentspace helps finance and legal teams handle compliance better. It monitors regulations and reviews documents automatically. Legal teams can watch regulatory processes without manual work. They run smart compliance checks and work better with business teams.

Finnit, another Google for Startups Cloud AI Accelerator member, offers AI solutions for corporate finance. Their system cuts accounting procedures time by 90% and improves accuracy. Legal departments can now work on strategic projects instead of processing documents repeatedly.

Google Agentspace Pricing and Deployment Options

Organizations need to understand the costs of google agentspace implementation to select the right tier based on their needs. Google provides three pricing tiers that offer different levels of features and capabilities.

NotebookLM for Enterprise ($9/user/month)

NotebookLM for Enterprise serves as the entry-level option. The tier has:

• A user interface that matches the consumer version
• Basic setup without pre-built connectors
• Support for Google and non-Google identity
• Sec4 compliance certification
• Cloud terms of service protections

NotebookLM Enterprise runs in your Google Cloud project. Your data stays within your environment and cannot be shared externally. This tier works well when we focused on document synthesis and analysis.

Agentspace Enterprise tier ($25/user/month)

The middle tier enhances NotebookLM's capabilities with detailed search features. Users get access to:

• Blended search across enterprise apps
• Document summarization tools
• Source material citations
• People search capabilities
• Search across text, images and other formats
• All NotebookLM Enterprise features

This tier acts as your company's source of truth through its branded multimodal search agent. The higher price brings many more features beyond simple document analysis.

Agentspace Enterprise Plus features ($45/user/month)

The premium tier helps realize the full potential of google agentspace as the most feature-rich option. Key features include:

• Follow-up questions for deeper exploration
• Actions in Google and third-party apps
• Document upload and Q&A interactions
• Tools to create custom automated workflows
• Research agents for gathering detailed information

Organizations can create expert agents at this level to automate business functions across departments like marketing, finance, legal and engineering.

Calculating total cost of ownership

The total cost calculation needs to factor in several elements beyond subscription pricing. Organizations should track:

• Infrastructure costs (CPU, memory, storage, data egress)
• Indirect costs (personnel, software tools, migration)
• Expected growth rates

The formula works by adding [(Cloud infrastructure costs) + (indirect costs) + (migration costs)] × estimated growth × timeframe.

Google Cloud's Migration Center provides tools to generate TCO reports. Teams can export these reports to Google Slides, Sheets, CSV or Excel formats to share with stakeholders.

Conclusion

Google Agentspace is changing how businesses work by combining powerful AI with enterprise search through its innovative architecture. In this piece, we looked at how companies can build custom AI agents, implement enterprise-wide search, and combine their business systems naturally.

The platform offers three pricing tiers that start at $9 per user monthly for NotebookLM Enterprise and go up to $45 for Enterprise Plus. This makes it available to companies of all sizes and needs. Success stories from Wagestream, Finnit, and major retailers show major improvements in efficiency and customer experience across their departments.

Key takeaways from our exploration include:

• Gemini-powered AI foundation enabling sophisticated reasoning and search capabilities
• No-code Agent Designer democratizing AI agent creation across skill levels
• Complete integration options with Google Workspace and third-party applications
• Reliable security measures ensuring data protection and compliance
• Measurable ROI across marketing, HR, IT, and finance departments

Google Agentspace alters the map of how enterprises handle information access and workflow automation. Current adoption trends and continuous platform improvements suggest this technology will become vital for organizations that want to stay competitive in an AI-driven business world.