Ziya ONEthe All-in-One AI platform.

One platform, many AI agents: they work in your documents and inside your systems, keep to your roles and permissions - and hand back the finished file, not just an answer.

  • GDPR-compliant
  • Made in Germany
  • Model-agnostic

Definition

What an enterprise AI platform is

An enterprise AI platform gives everyone in a company shared, controlled access to artificial intelligence: a suitable model per task, access to the company's own documents and systems, plus roles and permissions as in the rest of the IT. It differs from a public AI service in that where it runs, how the data is used and who may access it belong to the company.

Ziya ONE is that platform: with a data processing agreement, no use of your content for training, model-agnostic, on-premise or entirely off the network on request, and built on ZiyaOS so vertical use cases sit straight on top of it.

Your work sits in documents

Quotes as PDFs, costings in Excel, contracts in Word, analyses in PowerPoint. Ziya ONE reads those files as they are - sheets, paragraphs, page numbers - and works with what is inside them rather than with a summary of it.

And what comes back is a document too

An agent that only answers has merely moved the work. Ziya ONE agents produce the file you would have built anyway: the comparison table as XLSX, the report as DOCX, the review deck as PPTX. Versioned, shareable with the team, downloaded in one click.

Independent of any single model

GPT, Claude, Gemini or open models in your own data center: Ziya ONE is model-agnostic. When a better model appears, you swap the model layer, not your application.

Workflows

Runs that start without being asked

An agent somebody asks is one half. The other is work that starts on its own: in the workflow editor you connect a trigger, AI steps, branches and actions in your systems into one path that runs the same way every time - with a human approval exactly where it belongs.

  • Mail
  • Calendar
  • Chat
  • File storage
  • Wiki
Integrations

Connected to the systems you already work in

Connected once, a connection serves every agent: the same data, the same roles, the same permissions.

Talk about connecting yours
  • ERP
  • CRM
  • DMS
  • Database
  • Your API

The question most people arrive with

ChatGPT for business: the difference from a company account

Almost every rollout begins with the discovery that staff have been using ChatGPT for a while already - privately, uncontrolled, and with company data in it. That is not a discipline problem, it is a tooling problem.

Where the data goes
With the public service, input leaves the EU. Ziya ONE runs in the EU, in your own data centre if you want, or entirely off the network - with no seat minimum.
Whether it trains on you
Your content is not used to train models, and there is a data processing agreement saying so - not just a toggle in a profile.
Who may see what
Roles and permissions as in the rest of your IT. Sales sees sales documents, HR sees its own, and every answer names the source it came from.
Which model answers
Model-agnostic rather than tied to one vendor: which model handles a task is a setting, not a migration.

So the difference is not the interface - your people already know that part. It is everything happening behind it.

Frequently asked questions

What distinguishes Ziya ONE from a chatbot like ChatGPT?
A chatbot answers questions from its training knowledge. Ziya ONE agents work with your data and inside your systems: they read documents, access ERP and CRM, and complete entire work steps, with roles, permissions and citations.
Where does our data run?
Your choice: in ISO 27001-certified EU data centers, on-premise in your own infrastructure, or fully air-gapped without internet connection. Your data is never used to train models.
Are we tied to a specific AI model?
No. Ziya ONE is model-agnostic: GPT, Claude, Gemini and open models are interchangeable, even retroactively. You stay independent of individual vendors and can always use the best model for each use case.
How quickly is a first use case productive?
Typical first use cases such as an internal knowledge system or a report agent are productive within two to six weeks, because the platform already provides connectivity, permissions and operations.
What does Ziya ONE cost?
Costs depend on scope, deployment model and the number of use cases. In a free initial consultation we clarify your needs and give you a concrete estimate.

See Ziya ONE with your own data

We show Ziya ONE live on your own use cases - from the question in the chat to the finished file. Half an hour, free and without obligation.

Book a live demo