Gemini
Multimodal intelligence natively embedded in the Google Cloud ecosystem.
Best forTeams on Google Workspace or Google Cloud, and any business whose real problem is sitting in a data warehouse rather than a document.
Google Gemini 3.1 Pro is a multimodal AI model that processes text, images, audio, video, and code in a single system. Its deep integration with Google Cloud — including BigQuery, Vertex AI, and Workspace — makes it the natural choice for organisations already invested in the Google stack.
What Gemini does in the tools you already own
- Google Sheets, and your Excel files
- In Sheets, Gemini writes the formula, builds the analysis and explains what it did. The question we get asked more often is whether it touches Excel, and the honest answer is that it works on Excel files rather than inside the Excel application. Upload an xlsx and Gemini will read it, analyse it and hand back a cleaned version. If you need AI in the Excel ribbon itself, that is Copilot. If you need the analysis done and do not care which application it happens in, this works.
- BigQuery
- This is the one that changes numbers rather than saving minutes. Gemini runs inference inside BigQuery, so you classify, score and enrich data without exporting it anywhere. For anyone with POPIA exposure, keeping the data in the warehouse instead of shipping it to an external endpoint is worth more than the convenience.
- Gmail and Docs
- Drafting, summarising and thread catch-up in the places people already work. The same category of value Copilot delivers on the Microsoft side, and the reason the choice usually follows whichever suite you already pay for.
- Vertex AI
- Where the actual automation gets built: agents that plan and act, grounded in your own data, with region and retention set explicitly. Everything we put into production for clients on Google runs here rather than on a consumer surface.
- Grounding with Search
- Answers can be grounded in live web results rather than bounded by a training cutoff. Genuinely useful for anything price-sensitive or regulatory, where a confidently stale answer is worse than no answer.
What makes Gemini stand out
Multimodal Understanding
Process and reason across text, images, audio, video, and code in a single model — eliminating the multi-pipeline setups competing models still require. Gemini 3.1 Pro can ingest 900-page PDFs, one hour of video, or 8+ hours of audio in a single prompt.
Google Cloud Integration
Native integration with Vertex AI, BigQuery ML, Gemini Enterprise, and Google Workspace — reducing friction for teams already operating on Google infrastructure. Also available via AI Studio, Antigravity, Gemini CLI, and Android Studio.
Frontier Reasoning with Thinking Levels
Gemini 3.1 Pro introduces configurable thinking levels (low / medium / high) that let you balance cost, latency, and reasoning depth per request — delivering 2x the reasoning depth of Gemini 3 Pro and state-of-the-art performance on ARC-AGI-2 and GPQA Diamond.
Grounding with Search
Gemini grounds responses in real-time web data via Google Search, and supports Grounding with Google Maps, File Search, Code Execution, and URL Context as built-in tools — keeping answers current and verifiable rather than bounded by training cutoffs.
What we build with Gemini
Document & Image Analysis
Analyse invoices, forms, medical images, or engineering drawings alongside their associated text with high-fidelity multimodal reasoning — enabling end-to-end document automation at scale.
BigQuery ML Integration
Run Gemini-powered inference directly within BigQuery — scoring, classifying, and enriching data without moving it out of your warehouse.
Workspace Automation
Automate report generation, email drafting, meeting summaries, and document creation within Google Workspace using Gemini-powered agents, now extended to NotebookLM and Gemini in Chrome.
Vertex AI Pipelines
Build end-to-end ML pipelines on Vertex AI with Gemini 3.1 Pro as the reasoning layer — from data preparation to model deployment to monitoring, with Agentic tooling built in via Google Antigravity.
Gemini vs Microsoft Copilot
| Gemini | Microsoft Copilot | |
|---|---|---|
| Where it lives | Inside Docs, Sheets, Gmail, Meet and BigQuery | Inside Word, Excel, Outlook, Teams and SharePoint |
| Strongest use | Analysis and inference where the data already sits | Assistance where the documents already sit |
| Spreadsheets | Native in Sheets; reads and returns Excel files | Native inside the Excel application itself |
| SA data residency | Johannesburg region (africa-south1), service availability varies | South Africa datacentre regions available for the tenant |
| The deciding question | Is your problem in the warehouse or in the documents? | Is your problem in the warehouse or in the documents? |
What it costs, and where your data sits
How it licences
- Pricing model
- Two lines again. Gemini in Workspace is per user per month, either bundled into the Workspace tier or added on. Anything built on Vertex AI is consumption-based, priced per million tokens.
- Commitment
- Workspace follows your existing annual agreement. Vertex AI is pay-as-you-go.
- What this means in rand
- Because Google has moved Gemini into higher Workspace tiers over time, some businesses are already paying for it without having switched it on. Worth checking your current tier before buying anything: we have started more than one engagement by finding the licence was already there.
POPIA and data residency
Where it processes
Johannesburg region (africa-south1), with service availability to confirm
Google Cloud runs a Johannesburg region, which makes Gemini one of the more straightforward options for a business that wants processing to stay in the country. The qualifier that matters: having a region is not the same as having every service in it, and Vertex AI feature availability differs by region and changes over time. Confirm the specific models and services your workload needs are available in africa-south1 at design time rather than assuming. Where they are not, section 72 still permits cross-border processing with comparable protection or contractual cover. The strongest POPIA argument on this platform is architectural anyway: run inference inside BigQuery and the personal information never leaves the warehouse to begin with.
Why take our word for it
FICA compliance automation on Vertex AI
We automated regulatory onboarding checks for a South African neo bank on Google Vertex AI and BigQuery, with a daily aggregation pipeline and an audit trail of every automated decision kept for examination. Regulated work, in production.
Cloud data architecture for a neo bank
A full data estate on Google Cloud for a South African bank. When we recommend Gemini it is on the back of having built the warehouse underneath it, which is usually where the real problem turns out to be.
Gemini questions
Ready to put Gemini to work?
We'll help you identify where Gemini can create the most impact — and build it the right way, the first time.