Keep people in command while agents do the heavy cognitive work.
QUI lets agents reason, coordinate, and act inside boundaries defined by humans.
The Core Principle
The future of enterprise AI is not fully manual and it is not blindly autonomous.
The useful pattern is controlled autonomy: agents can move work forward, but humans define goals, authority, permissions, review points, and escalation.
What Humans Control
In QUI, humans and administrators can control:
- Which agents exist
- What roles they perform
- What knowledge they can access
- Which tools they can use
- Which channels they can respond through
- Which workflows they can execute
- Which model routes are allowed
- How much they can spend
- When they must pause
- When approval is required
Why This Matters
As agents become more useful, they create more operational impact.
That impact must be managed. Companies need agents that can help with real work without silently exceeding their authority.
QUI is designed around human checkpoints and explicit control surfaces, so companies can let agents do more without losing oversight.
Product Proof
ThinkThing Review Gates
Workflows can pause for approval, revision, or rejection.
Anima Permissions
Agent capabilities are configured through character-level controls.
Tool Boundaries
Terminal, MCP, web retrieval, M2M, and channel actions flow through controlled service paths rather than arbitrary frontend execution.
Budget Controls
Agentic loops and model calls can be bounded by token and cost limits.
Applied Use Cases
- Approve a customer response before sending
- Review a deployment plan before terminal execution
- Route financial analysis to a human before action
- Pause policy-sensitive workflows for legal review
- Require executive approval before external communication