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Gemini — AI native to Google Workspace.

For teams already deep in Google Workspace, Gemini is often the right primary AI platform. It is integrated into Gmail, Drive, Docs, Sheets, and Slides — no copy-paste, no context-switching. We deploy Gemini for Workspace, configure the deeper integrations, and build on Vertex AI for custom workloads.

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Why Gemini — what makes it different

Gemini's defining strength is integration. If your team lives in Google Workspace, Gemini is one click away inside every product they already use. Help drafting an email in Gmail, summarize a thread, generate a presentation from a doc, build a formula in Sheets — all without leaving the surface where the work is happening. For Workspace-native teams, this eliminates the friction that holds back AI adoption everywhere else: people forget to switch tools, or it is too much work, so the AI sits unused. With Gemini in Workspace, the AI is always there.

What we deliver

Gemini rollout, end to end.

Gemini for Workspace

The Workspace-integrated AI: Help me write in Docs, Help me visualize in Sheets, Help me organize in Gmail, generate slides from a doc. Per-user license through Workspace; identity inherited from your existing Workspace org.

Drive / Docs / Sheets deep integration

Gemini grounded in your Drive content: ask questions about specific documents, generate summaries, find policies in shared drives, draft from templates. We configure permission scopes so Gemini only sees what each user is supposed to see.

NotebookLM for research

NotebookLM is Google's research AI — give it a corpus of source documents and it becomes an expert on that corpus. Perfect for compliance teams (regulations + policies), sales enablement (product docs + competitive intel), customer success (account history + product knowledge).

Vertex AI for custom workloads

For custom apps and enterprise integrations: Gemini models on Google Cloud's Vertex AI platform. Production-grade with VPC isolation, customer-managed encryption keys, audit logging into Cloud Logging, integration with BigQuery for AI on your warehouse data.

Identity + governance

SSO inherited from Workspace, per-user data-loss-prevention rules, audit logging into Workspace Vault for compliance retention, admin console for usage governance.

Adoption + training

Workspace-specific training: how to use Gemini inside each product effectively, role-by-role patterns, the "I forgot it was there" friction-reduction techniques. Each role gets a focused 90-minute session.

Who Gemini is best for

Where Gemini wins, where it does not.

Where Gemini wins

  • Teams already in Google Workspace as primary collaboration suite
  • Document-heavy workflows where AI needs to live where the work lives
  • Research teams (NotebookLM is best-in-class for source-grounded research)
  • Teams running on Google Cloud (Vertex AI is the natural fit)
  • Long-context document analysis (Gemini has very large context windows)
  • Multi-modal work (Gemini is strong at video + audio + image together)

Where Gemini is NOT the answer

  • Microsoft 365–native teams (Copilot is integrated where they live)
  • Code-heavy engineering work (Claude Code is the agentic leader)
  • MCP-native tool use (Claude is the reference standard)
  • Maximum-breadth ecosystem (ChatGPT has the largest plugin catalog)

Education

What Gemini buyers should understand.

Why "where the work lives" matters more than model quality

The most common reason AI rollouts fail is not model quality — it is friction. If using AI requires opening another tab, signing in, copying context, then copying back, most employees will not do it. Gemini's defining advantage is that it lives inside Gmail, Drive, Docs, Sheets, Slides — the products your team already opens 50 times a day. The cumulative effect of "no friction" usually beats "slightly better model" for everyday productivity.

NotebookLM is genuinely different

NotebookLM is not a chatbot. It is a research tool: give it a set of source documents (PDFs, Drive docs, websites, audio files), and it becomes a domain expert on that corpus — citing every answer back to the source paragraph. Compliance teams use it on regulations + policies. Sales teams use it on product docs + competitive intel. Customer success uses it on the account history. There is no equivalent in the Anthropic or OpenAI catalog today; if your work involves "make AI an expert on this body of source material," NotebookLM is the right tool.

Why Vertex AI for custom — not the consumer Gemini API

The consumer Gemini API is the developer-facing entry point. Vertex AI is the enterprise platform: VPC isolation, customer-managed encryption keys, audit logging into Cloud Logging, identity integration with your existing Google Cloud org, AI on top of your BigQuery warehouse data, IAM-controlled access to model endpoints. For any production use case, Vertex AI is the right starting point.

The Gemini long-context advantage

Gemini supports very large context windows — millions of tokens — which means you can put an entire codebase, an entire deal data room, or hours of meeting transcripts into a single conversation. This unlocks workflows that other models cannot handle in one shot. We design specific use cases around this advantage where it materially changes the work (long-form contract analysis, multi-document synthesis, cross-source reconciliation).

Ready to make Gemini your team's AI?

Tell us your team size, the Workspace surfaces you want AI inside, and your timeline. We will come back with a written plan + quote within five business days.

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