AI provider
Google Gemini integration
Gemini handles text, images, audio, and video, and sits close to Google Cloud and Workspace. We use it where that closeness helps, and compare it with other providers so the choice follows the task and not the brand.
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- Building since 2010
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- 50+ technologies
At a glance
What it is
Gemini is Google's family of AI models, which can work with text, images, audio, and video, and is available through Google Cloud and Google's developer tools.
Problems it solves
Organizations already on Google Cloud or Workspace want AI features that fit their existing data, security, and billing, without a separate set of vendors.
Who it suits
Teams using Google Cloud or Workspace, and anyone with image, audio, or video material that needs reading or describing.
How to choose
Consider Gemini when your data and tools already sit in Google's ecosystem, or when the task mixes media types. Compare it on your own examples.
What it means
Models that read more than text
Gemini is a family of AI models from Google. Several versions can take text, images, audio, and video as input, and software reaches them through an API, a set of agreed requests, using Google's cloud or developer services.
Working across media matters for tasks like reading a scanned form with handwriting, describing a product photo, or summarizing a recorded call. One model can handle the whole item.
For organizations already on Google Cloud, there is a practical advantage: billing, access control, and data location can follow the rules they already use.
What DECHY can do
Working with Gemini
Assess
- Testing Gemini against your examples.
- Comparing it with other providers.
Build
- Document and image reading pipelines.
- Assistants connected to Google Workspace and your systems.
Control
- Access limits that follow your permissions.
- Human review for low-confidence results.
Run
- Deployment on Google Cloud, with cost alerts.
- Re-testing as models change.
Where it fits
When Gemini is worth testing first
These are the situations where we most often include it in a comparison.
Which sounds like your project?
Choose this when
Your data, identity, and billing are on Google Cloud.
- What you get
- AI features that follow your existing access rules, regions, and billing, with less new vendor work.
- Keep in mind
- Convenience is not quality. We still compare on your own examples.
Choose this when
Scans, photos, recordings, or video that people review by hand.
- What you get
- A pipeline that reads the media, extracts the facts, and flags what needs a person.
- Keep in mind
- Quality depends on the source. Poor scans and noisy audio need testing early.
Choose this when
Your team works in Docs, Sheets, Gmail, and Drive.
- What you get
- Assistants and automations that work with files and messages where your team already works.
- Keep in mind
- Permissions need care. An assistant should see only what its user may see.
Alternatives
Gemini compared with other providers
| Consideration | Where Gemini may help | Where to check |
|---|---|---|
| Ecosystem | Close to Google Cloud and Google Workspace. | Less natural if your stack is elsewhere. |
| Media types | Built to take mixed input. | Quality on your particular media. |
| Alternatives | OpenAI and Anthropic Claude are strong options. | Run the same examples through each. |
| Open models | Not applicable. | Open models can run in your own environment when data cannot leave it. |
Typical uses
Work that suits mixed media
Reading scanned forms and receipts
Extracting names, dates, and amounts from paper that was scanned or photographed, and flagging the unclear ones.
Describing product and site images
Writing descriptions and tags for large image libraries, with a person reviewing a sample.
Summarizing recorded calls
Turning audio into a short record of what was agreed and what needs follow-up.
Answering questions across Workspace files
Finding information in documents, sheets, and email, within each person's own permissions.
Technical depth
How we build with Google Gemini
The detail a technical reviewer will ask about: access routes, pipeline design, and evaluation.
Gemini can be reached through Google's developer service or through Vertex AI on Google Cloud. We usually prefer the cloud route for business work because identity, regions, and billing follow your existing set-up.
- Structured output validated against a schema before use.
- Queues for batch work such as scanning a backlog of documents.
- Storage of originals alongside extracted results, so any result can be traced back.
We build a labeled sample of your real material, score each provider's output against it, and re-run the sample on every change.
Common questions
Questions about Gemini
Do we need to be on Google Cloud to use Gemini?
No. It can be called from anywhere. Being on Google Cloud makes identity, billing, and data location simpler.
Can Gemini read handwriting and scanned forms?
It can read many of them well. Quality depends on the scan, so we test early on your real examples.
How do you keep data private?
We review the provider's current terms, choose regions and settings that fit your rules, and send only the data the task needs.
Can we combine Gemini with other models?
Yes. Many systems use a smaller, cheaper model for simple steps and a stronger one for hard ones, sometimes from different providers.
Have a different question?
Tell us what you are weighing up and we will answer it plainly.
Ask a questionAlready a client? Email support@dechytech.com
Tell us where your data lives
Describe the material, the task, and the tools you already use. We will test Gemini and the alternatives and recommend one on the results.