AI that operates across your entire Google ecosystem — Gmail, Docs, Sheets, Drive, and Vertex AI.
Google Gemini brings AI into Google Workspace and Vertex AI. DeployLabs builds coordinated agent systems that go beyond Gemini's default capabilities — connecting your Gmail, Drive, and Sheets data into automated workflows that produce real business output.
What Google Gemini brings to your operations.
Workspace Integration
Gemini operates natively in Gmail, Docs, Sheets, Slides, and Meet. DeployLabs configures workflows that chain these together — draft emails in Gmail, pull data from Sheets, generate reports in Docs, and summarize meetings in Meet, all coordinated by agents.
Vertex AI Platform
Google's Vertex AI provides enterprise-grade model deployment, fine-tuning, and orchestration. For businesses on Google Cloud, this means AI that runs within your existing infrastructure with GCP's security and compliance controls.
1M Token Context Window
Gemini 1.5 Pro processes up to 1 million tokens in a single context — enough to analyze hundreds of pages of contracts, entire email archives, or full project repositories in one pass. No chunking, no summarization loss.
Multimodal Understanding
Gemini processes text, images, video, and audio natively. For businesses handling visual content — site inspections, product photos, video transcripts — this eliminates manual review and classification steps.
The platform gives you the foundation. We build the engine.
Google Gemini provides
- Gemini in Google Workspace (Gmail, Docs, Sheets, Meet)
- Vertex AI for enterprise model deployment
- 1M token context window for long documents
- Multimodal processing (text, image, video, audio)
- Google Cloud security and compliance controls
- AI Studio for prototyping and testing
DeployLabs adds
- Workflow automation connecting Workspace apps
- Vertex AI agent configuration for your domain
- Google Drive knowledge base structuring
- Custom prompt engineering for your business processes
- Cross-platform integration with non-Google tools
- Performance monitoring and optimization
Three phases. No templates. No shortcuts.
Assess
We map your Google Workspace usage patterns, audit your Drive data organization, and identify where Gemini agents create the most operational leverage. The assessment covers both Workspace AI and Vertex AI opportunities.
1–2 weeksBuild
Gemini agents are configured for your workflows, Drive knowledge bases are structured for agent consumption, and Vertex AI pipelines are deployed within your GCP project. Each workflow is tested against real scenarios from your operations.
4–8 weeksOperate
Ongoing monitoring tracks Gemini adoption, output quality, and Vertex AI usage costs. Monthly reviews optimize configurations, expand workflows, and ensure your Google AI investment is producing measurable returns.
OngoingGoogle Gemini engines built for your industry.
Measured results from Google Gemini engine deployments.
Enterprise-grade security built into every deployment.
Google Cloud Security
Vertex AI runs within your GCP project with IAM controls, VPC Service Controls, and Customer-Managed Encryption Keys. No data crosses project boundaries without explicit configuration.
SOC 2 · ISO 27001 · FedRAMP · HIPAAWorkspace Data Controls
Gemini in Workspace respects your existing sharing permissions, data regions, and DLP policies. Admin controls manage which features are available to which users.
Google Admin Console · DLP · Data RegionsNo Training on Your Data
Google Workspace and Vertex AI do not use your data to train foundation models. Enterprise agreements include contractual guarantees on data handling and processing boundaries.
Google Cloud Data Processing TermsCanadian Data Residency
Google Cloud offers Canadian regions (Montreal, Toronto) for data residency. Vertex AI models can be deployed within Canadian infrastructure to meet data sovereignty requirements.
PIPEDA · Provincial Privacy Acts · Data SovereigntyWhat clients ask about Google Gemini.
We use Google Workspace — is Gemini worth the add-on cost?
Gemini for Workspace adds $20 USD/user/month. Without configuration, most teams use it for basic email drafting and get minimal ROI. With DeployLabs, Gemini becomes a coordinated system — automated email workflows, intelligent document generation, data-driven reporting from Sheets, and meeting action tracking. The difference is ad hoc usage vs. systematic deployment.
How does Gemini compare to Copilot for M365 users?
If your organization runs on Google Workspace, Gemini is the native choice — same way Copilot is native for Microsoft 365. The models are comparable in capability. The integration depth with your existing tools is what matters most. We assess your stack during the readiness assessment and recommend the best fit.
What does a Gemini deployment cost?
The AI Readiness Assessment is $2,500. Custom agent builds start at $7,500. Monthly optimization retainers range from $2,000 to $5,000. Google licensing (Workspace AI add-on + Vertex AI consumption) is separate and varies by usage volume.
Can Gemini connect to non-Google tools?
Yes. Vertex AI connects to any system via API. DeployLabs builds integration layers between your Google ecosystem and external platforms — Salesforce, HubSpot, QuickBooks, industry-specific tools. The Google ecosystem handles the core, and API connections extend to everything else.
Is the 1M token context actually useful for business?
For most single-query tasks, 200K tokens is sufficient. The 1M context window matters for specific use cases: analyzing entire contract portfolios, processing full project documentation sets, or reviewing months of email correspondence in a single pass. We identify which of your workflows benefit from extended context during the assessment.
Ready to build your Google Gemini engine?
Start with a free discovery call. We map your operations and show you exactly where Google Gemini creates the most leverage for your business.