Zy-AI
Use company knowledge with answers your team can check.
Give teams one place to ask questions and complete supported work using approved information. Keep access, sources, and important activity visible.
Why Zy-AI
The model creates the response. Zy-AI makes it useful for your business.
An AI model is the engine that reads a request and generates a response. By itself, it does not know which company information a person may use, how your teams are separated, what needs approval, or what should remain visible afterward.
1Response engineYour chosen AI model
Provides language and reasoning through the provider account you configure.
2Business operating layerZy-AI
Adds approved information, workspace access, memory, tools, review steps, sources, and activity history.
3People stay responsibleYour team's work
People ask questions, complete supported tasks, review results, and make important decisions.
Model + company context + people
Zy-AI does not replace the model. It turns the model you choose into a company workspace built around your information, people, and way of working.
What is available now.
See the current version, who it is for, and how it can be set up for your organization.
Published releaseZy-AI v1.4.1Published September 26, 2026
Available for
Guided demonstrations and small pilot setups.
Where it runs
A dedicated setup with private data storage and the customer's chosen AI provider.
What teams can do
- Ask questions using approved company information.
- Separate teams, information, and permissions by workspace.
- Use supported AI models through customer-controlled provider accounts.
- Keep useful context across work instead of starting from zero each time.
- Review sources, important actions, approvals, and history.
What it is not
Zy-AI is not a system that should act without people, replace management judgment, or resell AI usage. The provider, hosting, data access, and approval steps are agreed for each setup.
Best starting point
Choose one important question or approval task, identify the people and information involved, then test the result in a working demonstration before expanding.