GOOGLE CLOUD · ENTERPRISE AI
Gemini Enterprise consulting and implementation, connected to your company's knowledge and processes.
We plan and implement Gemini Enterprise so scattered corporate data becomes search, analysis, and agents that are useful in daily work.
DIRECT ANSWER
What is Gemini Enterprise?
Gemini Enterprise is Google Cloud's agent platform for connecting AI, corporate data, search, and automation in a single governed experience for the enterprise.
Who it is forCompanies that need to make internal knowledge available, automate workflows, or build agents with access controls and corporate governance.
CONTEXT
What Gemini Enterprise is and how to adopt it in your company
Deployment starts with the problem, not the tool. We identify recurring questions, repetitive processes, data sources, and user groups to define where AI can produce measurable value.
Then we connect repositories and applications, design the agents, configure permissions, and build an evaluation layer. Answers have to be useful, traceable, and consistent with the access each person already has.
EAGLE BS combines experience in Google Cloud, software, data, and security to take the initiative from pilot to an operation tracked by usage, quality, and impact metrics.
IN DEPTH · 1/4
Gemini Enterprise at a glance: platform, origin and scope
An agent platform from Google Cloud
Gemini Enterprise brings an AI assistant, search over corporate data and agents into one experience built for companies, with identity and access controls.
From Google Agentspace to Gemini Enterprise
Google brought Agentspace and new capabilities together into the Gemini Enterprise platform. Any deployment should follow Google Cloud's current naming and product portfolio.
What it connects
The platform connects corporate sources such as document repositories, wikis, ticketing systems and internal applications, depending on the connectors available for your environment.
Who it is for
For companies that want people to find information, summarize, analyze and automate tasks with AI without exposing data to people who should not see it.
IN DEPTH · 2/4
What happens at each stage of the deployment
A good deployment starts with the problem, not the license.
Use cases and users
We identify recurring questions, repetitive processes and user groups to define where AI creates measurable value.
Connectors and permissions
We map the data sources and configure identity and access control, so the AI only consults what each person is allowed to see.
Agents tied to processes
We build agents for specific tasks, connected to the systems where the work happens, with limits and action logs.
Quality evaluation
We assemble a set of test questions to measure whether answers are useful, correct and based on verifiable sources.
Adoption and training
We support the team with usage guidance and track what is actually used, adjusting what does not create value.
IN DEPTH · 3/4
Gemini Enterprise or a custom solution: how to choose
It is not an either-or choice. The question is how much customization the use case needs.
Gemini Enterprise
Right when the goal is to give many people AI search and assistance over company knowledge, with a ready-made, governed experience.
Custom agents and applications
Right when the result is your own product or workflow, with specific rules, deep integrations or its own interface.
Custom RAG
Right when information retrieval needs special rules for chunking, permissions or evaluation.
A combination
It is common to use the ready-made platform for most people and build custom solutions for the few cases that need more.
IN DEPTH · 4/4
Security and governance in Gemini Enterprise
Identity and access
Integration with the company's identity system defines what each person can query. We review it before any data source is connected.
Data policies
Retention, residency and use of data follow the contract with Google Cloud and should be reviewed by your legal and security teams.
Logging and audit
Agent actions and platform use should be logged, to investigate problems and demonstrate compliance.
Human review
Agents that act on systems operate with limits and human approval at the higher-impact steps.
OUTCOMES
What Gemini Enterprise needs to deliver
Technical goals only matter when they improve security, speed, cost, experience or the ability to decide.
- 01Unified search across corporate knowledge
- 02Agents wired into real processes
- 03Answers with context and sources
- 04Less time spent looking for information
- 05Access governance
- 06Evaluation-driven iteration
WHEN IT MAKES SENSE
When it makes sense to deploy Gemini Enterprise
- Information is scattered across many systems
- Teams repeat the same questions and tasks
- There is demand for internal agents with security
- AI pilots never reached production
- The company wants to adopt AI without exposing data
- AI has to be integrated into existing applications
HOW WE WORK
How we deploy Gemini Enterprise, from use case to scale
Short stages, visible criteria and knowledge transfer at every decision.
Use cases
We prioritize problems by impact, feasibility, and risk.
Data and access
We map sources, quality, identity, and permissions.
Agents and integrations
We build experiences connected to corporate workflows.
Evaluation and scale
We measure quality, adoption, cost, and continuous improvement.
DELIVERABLES
What you receive in a Gemini Enterprise deployment
- Use case map
- Data and access architecture
- Gemini Enterprise configuration
- Agents and connectors
- Evaluation suite
- Adoption and governance plan
TRACK RECORD
Experience with Google Cloud and AI agents
More than 10 years of Google partnership, AI projects in production and one of the early certified Google Agentspace partners in Brazil, now part of Gemini Enterprise.
- 10+
- years of Google partnership
- 170+
- projects delivered
- Agentspace
- one of the early certified partners in Brazil
FREQUENTLY ASKED QUESTIONS
Frequently asked questions about Gemini Enterprise
What is Gemini Enterprise?
It is Google Cloud's AI agent platform for companies. It brings an AI assistant, search over corporate data and agents into one governed experience, with identity and access controls over the data.
How much does Gemini Enterprise cost?
Pricing is set by Google Cloud and depends on the edition, the number of users and usage. EAGLE BS helps size the scope and compare scenarios before purchase, and the investment for the implementation project is presented in an individual proposal.
Gemini Enterprise or another enterprise AI platform?
It depends on the company's ecosystem, data, required governance and use cases. We compare the alternatives with concrete criteria before recommending, without starting from a chosen tool.
How long does it take to deploy Gemini Enterprise?
It depends on how many data sources are connected, permissions and integrations with systems. We start with a few use cases and sources to evaluate quality before expanding, and the timeline is set after that stage.
Did Gemini Enterprise replace Google Agentspace?
Google brought Agentspace and new capabilities together into the Gemini Enterprise platform. Any deployment should follow Google Cloud's current naming and product portfolio.
Can it connect to internal data?
Yes. The project defines sources, connectors, permissions, and access rules so the AI only queries what each user is allowed to use.
Is the platform only for search?
No. Beyond search and summarization, agents can support analysis and take actions in integrated systems, always with the right controls.
How do we know the deployment worked?
We define metrics for answer quality, time saved, adoption, task completion, cost, and security before expanding usage.
Technical sources and references
FIELD EVIDENCE
AI evaluated rigorously and wired into infrastructure.
Reproducibility, LLM evaluation, data, agents and operations are treated as parts of one system.
Artificial Intelligence
MLRC 2025 at Princeton: five principles for reproducible LLM evaluation
Five EAGLE BS lessons from MLRC 2025 at Princeton AI Lab on benchmarks, determinism, data, transparency, and robust LLM evaluation.Read article ↗
Google Cloud
Google Cloud Next 2025: AI, agents, and the new digital infrastructure
EAGLE BS at Google Cloud Next and Partner Summit 2025: Agentspace, Gemini 2.5, agents, cloud, data, and practical lessons for customers.Read article ↗TALK TO A SPECIALIST
Tell us the situation. We help you see the best path.
A focused conversation to understand context, risk, priority and the first workable step.