What is Google Gemini?
Gemini is the family of AI models developed by Google. People can use Gemini as an app; developers can connect the models to their own software through the Gemini API. The API is accessed through Google AI Studio or, for enterprise use, through Vertex AI on Google Cloud. Gemini is designed as a multimodal model family, meaning it can process different kinds of content such as images and documents together with text.
A Gemini integration connects these capabilities to your website, your internal applications or your data infrastructure on Google Cloud through a controlled middleware layer.
What do we connect with Gemini?
| Data | Direction | Frequency |
|---|---|---|
| Product image and basic information | IMFLEXI / ERP → model → description and feature draft | As needed |
| Scanned document, form, delivery note | System → model → structured fields | When uploaded |
| Customer request | Form / email → model → classification | On arrival |
| Internal knowledge base | Approved documents → model → answer in plain language | When a question is asked |
| Activity log | Middleware → log | On every call |
Typical scenarios
- Product content generation: The images and technical details of new products are given to the model; drafts are produced for the product description, feature list and SEO title, and the content team edits and approves them. With the IMFLEXI AI-powered SEO feature, this flow lives inside the admin panel.
- Turning paper into data: A delivery note or service form photographed in the field is read, and its fields are filled in ready to be transferred into the system; an employee checks and approves.
- Data on Google Cloud: For a company whose data already sits on Google Cloud, the model is used from within the same environment, under enterprise access rules.
Globya's approach
We build Gemini and other model integrations as part of our AI-powered software service. The Globya assistant on our own site shows how AI can work with approved information and clear limits.
- Measurable benefit: How long the task takes today and how much AI will shorten it are measured from the start.
- Human approval: Content that gets published and data that is written into systems goes through approval.
- Model independence: The same middleware can also work with OpenAI or Anthropic Claude.
How do we work?
- Analysis: We define the task, the data to be used, the access route (AI Studio or Vertex AI) and the expected accuracy.
- Mapping: The fields sent to the model are chosen, personal data is masked, and instructions and output format are written.
- Test environment: It is tried on real examples and the results are scored with your team.
- Go-live: It is switched on in draft-and-approval mode.
- Monitoring: Every call is logged; on errors or timeouts the request is retried; accuracy and cost are reported regularly.
What to prepare before we start
- The task you want to automate and how long it takes today
- Whether you use Google Cloud or Google Workspace
- The type of data involved: text, images, scanned documents
- Where the output will go and who will approve it
- Your company rules on where data may be processed
With this information we decide on the access route (AI Studio or Vertex AI) and the scope of the first trial.
Security, cross-border transfer and KVKK
Google is a service provider headquartered abroad; data sent to the model may be processed outside Türkiye. For enterprise use, options such as the data processing region can be evaluated on the Google Cloud side; we look together at what that means in your case. Before personal data is sent, we assess whether it is needed and mask it where possible; if necessary, the cross-border transfer rules and the notice obligation under KVKK (Türkiye's Personal Data Protection Law) are addressed. Access keys and service accounts are set up on the principle of least privilege and kept in a restricted configuration, not in the code. For background, see AI and company data.
To talk about your AI project, call +90 850 432 55 13 or use the contact page. Pricing follows a written proposal after the discovery call. Describe your needs now in 3 minutes
Frequently asked questions
We use Google Workspace. Does Gemini integration come automatically?
The Gemini features inside Workspace are a separate matter. Connecting Gemini to your own systems requires a separate setup through the API or Vertex AI.
AI Studio or Vertex AI?
AI Studio can be enough for quick trials and small projects; if you need enterprise access rules and Google Cloud infrastructure, Vertex AI is the better fit. We decide based on your needs.
Is generating product descriptions from images reliable?
It is fast and useful for drafts; technical values and claims must always be checked by a person.
Will our data be used to train the model?
That depends on the service you use and the current terms. We review the terms together before setup.