For AI Product Teams
Build the Control Plane for an AI Product
Make model behaviour, tool execution, knowledge sources, costs and human approvals understandable to operators.
An AI product dashboard needs operational transparency: which model ran, which tools it called, what sources it used, how much it cost and where a human approved or corrected the result.
For AI startups, internal AI platform teams and agent-product developers.
The screens it needs
- Agent Directory — Ownership, status, model, tools and deployment.
- Run Detail — Steps, tool calls, sources, latency, tokens and errors.
- Prompt Library — Versions, environments, testing and rollback.
- Knowledge Sources — Documents, sync state, freshness and permissions.
- Evaluations — Datasets, graders, scores and regression history.
- Usage and Cost — Spend by model, agent, workspace and customer.
The workflow they sit in
- 1. Configure Agent
- 2. Connect Tools
- 3. Add Knowledge
- 4. Test
- 5. Approve
- 6. Monitor
Questions
Does VuiAdmin provide an AI model?
No. It provides interfaces for AI products and coding-agent guidance for building them. You select and integrate the model provider.
Can I show streaming responses?
Yes. The AI chat patterns cover composition, message history, code and progressive response states. Your API supplies the stream.
How are risky agent actions handled?
Use an explicit approval state, clear action description and audit entry before executing high-impact operations. Enforcement belongs in your backend.