Google Cloud Commercial and Professional Services Brazil

Grupo Dreamers

Enterprise Knowledge Search

Grupo Dreamers had 20 companies using fragmented AI tools and tech contracts without central governance, which trapped knowledge in silos and created legal, reputational, and IP risk from employees putting sensitive client data into unmanaged free AI services.

Collective knowledge now shared across all 20 companies
Gemini Enterprise deployed to 100% of 2,000 employees
Seventy percent of business units were using AI through personal or free accounts with no central governance.
Sixty two percent of technology contracts were fragmented

Reported impact

Business outcome

Grupo Dreamers deployed Gemini Enterprise to all 2,000 employees, consolidated fragmented technology contracts into one group agreement, reduced shadow-AI risk, and made prompts, knowledge, and reusable AI assets available across 20 companies.

  • Compliance
  • Productivity Improvement
  • Risk Reduction
  • Speed to Market

Solution

Grupo Dreamers standardized its internal AI stack on Google Workspace and Gemini Enterprise so employees across more than 20 media and entertainment businesses could move from shadow AI to a governed enterprise platform. The rollout uses native Gemini integration inside Gmail, Google Docs, Google Slides, and Google Meet, allowing teams to adopt AI through familiar collaboration tools instead of separate consumer apps. Access is structured in tiers: all employees receive productivity and summarization support, business specialists use advanced strategic research and multimodal creation, and engineering teams use the platform for deeper reasoning and code automation. The group also built an enablement model through Projeto Aurora and Academia Dreamers so knowledge, prompts, and automation patterns remain inside the holding. This architecture ties secure AI usage back to the group's existing Google Cloud data infrastructure and replaces fragmented tooling with one managed operating model.

Data flow

Employees work inside Google Workspace applications where Gemini Enterprise provides governed summaries, research, multimodal creation, and code support; prompts and outputs stay within corporate controls and can be reused across the holding instead of remaining in isolated personal tools or teams.

Solution architecture

7 components · 3 layers
  1. Compute
    • Gemini Enterprise Delivers protected enterprise AI for summaries, research, multimodal creation, and code assistance.
  2. Storage
    • Google Cloud Provides the underlying data infrastructure the group is expanding with predictive and generative AI.
  3. Serving
    • Google Workspace Provides the familiar productivity suite used as the rollout surface for governed AI adoption.
    • Gmail Acts as one of the native interfaces where employees access Gemini in daily work.
    • Google Docs Supports governed content creation and knowledge work with embedded Gemini assistance.
    • Google Slides Supports presentation creation and reuse of institutional knowledge across the group.
    • Google Meet Extends enterprise AI assistance into meetings and collaboration workflows.

Architecture clues

  • Access is structured across three tiers for operational staff, business specialists, and data or engineering teams.
  • Gemini is embedded natively in Workspace apps rather than introduced as a separate tool.
  • The group is extending the same platform toward predictive and generative AI on top of its Google Cloud data estate.
  • The rollout is phased through Projeto Aurora rather than a one-shot deployment.

Evidence from the source

Gemini Enterprise arrives natively embedded in Gmail, Google Docs, Google Slides, Google Meet, meaning employees don’t need to learn a new tool from scratch.
Gemini Enterprise deployed to 100% of 2,000 employees
Knowledge that used to disappear when an employee left, a brilliant prompt, an agent built for one client, now belongs to the group and stays available to everyone.
Seventy percent of business units were using AI through personal or free accounts with no central governance.
The answer was not to block AI but to replace it with something better.
Transparency Evidence & methodology 90/100 reference value · 79% confidence · 1 source

Review how this reference was scored and trace each normalized claim back to its documented source.

01

Scoring methodology

How scores are calculated

Customer Reference Value measures usefulness as a customer reference. Evidence Confidence measures the quality and traceability of available evidence, not independent verification.

Customer reference value90/100
  • Problem clarity20/20
    Measures whether the customer's operational problem is specific enough to compare.
  • Implementation depth25/25
    Rewards named components, data flow, integrations, and architecture detail.
  • Outcome specificity20/20
    Measures whether the reported benefit is concrete rather than a generic claim.
  • Quantified impact15/25
    1 metric describe measurable impact.
  • Deployment scale10/10
    Rewards evidence of a live or scaled deployment and meaningful integration scope.
Evidence confidence79%
  • Source authority20/25
    The main evidence is an official vendor-published customer story.
  • Claim traceability21/25
    10 of 12 key fields link to a named source.
  • Direct evidence20/20
    5 direct source quotes retained.
  • Date provenance0/10
    The publication date has no documented provenance.
  • Source transparency8/10
    1 source reference document publisher, URL, authority, retrieval, and supported fields.
  • Implementation specificity10/10
    Rewards source-backed components, data flow, quantified impact, and a specific outcome.
02

Traceability

Sources & provenance

Field coverage shows which facts each source supports. Dates are shown only when documented by the source.

  1. Google Cloud

    Grupo Dreamers customer story

    First-party
    https://cloud.google.com/customers/grupo-dreamers
    Source type
    Vendor-published customer story
    Supports
    • Customer
    • Business problem
    • Solution
    • Products
    • Solution components
    • Data flow
    • Integrations
    • technical area
    • use case category
    • Business outcome
    • outcome category
    • Metrics
    • Architecture
    • evidence quotes

Date evidence

  • Sitemap last modified Sep 2, 2026 · Google Cloud · Publisher metadata Publisher-reported modification timestamp; not a publication date.
    Open date source
  • Unverified extracted date Sep 2, 2026 · Google Cloud · Unknown Legacy extracted date without source-page confirmation.
    Open date source
Not separately sourced Industry, Region, Company size. Treat these normalized attributes as lower-confidence until a dedicated source is added.

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