Vertex AI and Gemini models
Access Gemini and other models through Vertex AI for generation, summarising, classification and chat inside your own applications.
Google Cloud AI · India
Google Cloud AI on your own data, with cost and security under control.
Google Cloud offers Gemini models through Vertex AI, plus Gemini Enterprise for search and agents across company data. The hard part is rarely the model: it is choosing a use case, preparing the data, setting guardrails and keeping usage costs predictable.
We help Indian businesses go from an idea to a working, governed AI workload on Google Cloud, starting small and measuring the result.
Why Rua
What a structured AI project avoids.
The common reasons early AI pilots stall or overspend.
A use case tied to a numberWe pick one workflow with a clear before-and-after, such as support triage or document review, so you can judge value quickly.
Security and data controlsProject structure, access roles, logging and data location decisions made at the start, with attention to DPDP obligations.
Costs you can predictUsage-based billing can surprise teams. Budgets, quotas and alerts are configured before the pilot reaches real users.
What we set up
Google Cloud AI services we help with.
Availability of specific models and features varies by region and over time; we check this at design stage.
Gemini Enterprise
Search and agents across company documents and systems, with your existing permissions respected.
Document and data workflows
Pull structured data out of invoices, forms and contracts, and feed it into your systems.
Data foundation
Clean, well-structured data in BigQuery and Cloud Storage so AI answers are grounded in your facts.
Gemini Code Assist
AI coding help for development teams, rolled out with sensible access and review practices.
Governance and cost
IAM roles, audit logging, budgets and quotas so the project stays secure and affordable.
Related: BigQuery setup, Google Cloud Platform and Gemini for Google Workspace. Background reading: AI agents for business, AI security guide and DPDP Act compliance.
How we work
From idea to a governed pilot.
Choose the use case
Workshop to rank ideas by value, feasibility and data readiness.
Prepare the data
Connect and structure the sources the AI will draw on.
Build the pilot
Prototype with guardrails, test on real examples and measure results.
Deploy and govern
Roll out to users with budgets, monitoring and a review cadence.
Planning a Cloud Transition? Avoid resource architecture inefficiencies. Download our Free Azure Cost Optimization Checklist to isolate license overhead pre-migration.
Coverage
Serving businesses across India.
Google Cloud AI projects are delivered remotely for businesses anywhere in India.
We serve businesses across India, with on-site support where needed and remote support everywhere. Get in touch to confirm coverage for your location, or browse IT services by city.
FAQ
Common questions about Google Cloud AI.
QWhat is the difference between Gemini in Workspace, Vertex AI and Gemini Enterprise?
Gemini in Workspace adds AI to Gmail, Docs, Meet and other apps. Vertex AI is the Google Cloud platform for building your own AI features with Gemini and other models. Gemini Enterprise focuses on search and agents across company data. Many organisations use more than one.
QHow is Google Cloud AI priced?
Vertex AI is generally usage-based, so cost follows how much your application is used, while Gemini Enterprise is licensed per user. We configure budgets, quotas and alerts and estimate costs before you scale.
QCan our data stay in India?
Google Cloud has regions in India, but which models and features are offered in a given region changes. We check availability and data-location requirements at design stage, alongside your DPDP obligations.
QDo we need our own data science team?
Not for a first pilot. We help with design and build, and we show your team how to run it afterwards. Larger programmes often benefit from an internal owner.
QCan the AI answer questions using our own documents?
Yes. This is a common starting point: connect approved document sources, apply your access permissions and test answer quality on real questions before wider rollout.
QDo you also help with the data side?
Yes. See our BigQuery setup service for structuring and connecting the data AI projects depend on.
Exploring AI on Google Cloud?
Tell us the workflow you want to improve and where your data lives, and we'll suggest a pilot — no obligation.
