Gemini & AI
Generative AI that is useful, connected to your data and under control.
We help you choose the right level of solution, from the assistant built into your tools to a custom application, and deploy it securely.
Three ways to use Gemini
These offerings meet different needs. Telling them apart avoids paying for capabilities you do not need, or building what already exists.
Gemini in Google Workspace
Assistance built into Gmail, Docs, Sheets, Slides, Meet and Drive: draft, summarise, analyse a sheet, prepare a meeting. Availability depends on your Workspace edition. Our role: configuration, sharing rules, training and adoption tracking.
Gemini Enterprise
A single entry point for your employees: search across authorised company sources, query documents and use ready-made or custom agents for your processes. Our role: connectors, access rights, agents and rollout.
Custom solutions on Google Cloud
When the need is specific: business applications, high-volume document processing, integration with your systems. We build on Gemini Enterprise Agent Platform (formerly Vertex AI), Gemini models, Document AI and BigQuery.
Use cases
For each case we state what is put in place, with which Google building blocks, and what needs the most attention.
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Search and assistant over internal documents
- For
- Legal, HR, quality and support teams
- What we put in place
- An assistant that answers questions from your procedures, contracts and knowledge bases, citing its sources.
- Google building blocks
- Gemini Enterprise, or a custom application on Gemini Enterprise Agent Platform
- Key consideration
- Quality and freshness of source documents; respecting access rights.
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Document information extraction
- For
- Finance, procurement, operations
- What we put in place
- Automatic reading of invoices, purchase orders or forms, extraction of the relevant fields and checks before integration.
- Google building blocks
- Document AI, Gemini models, BigQuery
- Key consideration
- Variety of formats and human review of uncertain cases.
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Support for sales, service and operations teams
- For
- Sales, customer service, field teams
- What we put in place
- Meeting preparation, customer history summaries, suggested replies and structured call notes.
- Google building blocks
- Gemini in Google Workspace, Gemini Enterprise
- Key consideration
- Controlled access to customer data and review before sending.
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Automation and integration with business applications
- For
- IT and business teams
- What we put in place
- Agents that chain tasks (classify, summarise, open a ticket, update a record) using your APIs.
- Google building blocks
- Gemini Enterprise Agent Platform, Cloud Run, your application APIs
- Key consideration
- Limited scope of action, logging and approval of sensitive actions.
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Data analysis and reporting
- For
- Management, finance, marketing
- What we put in place
- Centralised metrics and dashboards, with natural-language questions over prepared data.
- Google building blocks
- BigQuery, Looker, Gemini assistance
- Key consideration
- Shared metric definitions and upstream data quality.
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Productivity in Google Workspace
- For
- All employees
- What we put in place
- Drafting and summarising in Gmail and Docs, analysis in Sheets, note-taking in Meet, with clear usage rules.
- Google building blocks
- Gemini in Google Workspace
- Key consideration
- Training, use cases per team and adoption tracking.
Security and governance from the start
An AI assistant is only useful if it can be trusted. We address these topics before the pilot, not after.
- Data access inherits existing permissions: employees only find what they are already allowed to see.
- Hosting region and services chosen according to your regulatory constraints (Morocco’s Law 09-08, the UAE federal data protection law).
- Test sets and quality criteria defined with your teams to measure answer relevance.
- Human review for sensitive decisions and logging of usage.
- Training for users and administrators, with clear usage rules.
Our method
Four stages, each ending with a decision point.
Scoping
Goals, users, available data, security constraints and measurable success criteria.
Pilot
A first version on a limited scope, tested by real users, with results measured.
Deployment
Hardening, integration with your tools, security, documentation and team training.
Ongoing support
Operations, usage and quality monitoring, enhancements and cost optimisation.
Identify your first use case
A scoping call lets us check data availability, feasibility and expected value before any commitment.