Solvers help you monitor quality, apply SPC, manage equipment, and ensure traceability.
AI that helps quality teams get in control
Recognized by industry analysts. Prototypes validated with customers.
AI in AlisQI is not a feature layer or a future promise. It is applied to the problems quality teams face every day — where scale, complexity, and risk exceed human capacity alone.
A paper checklist, an Excel inspection sheet or a short description of the form you need.
Upload it. Or describe it in plain language.
AlisQI's AI analyzes the structure, identifies fields and data types, understands basic logic, and generates a fully structured digital form inside your system.
No manual rebuilding.
No technical setup.
What used to be a configuration job becomes a starting point ready for refinement.
Quality systems contain answers. Finding them usually means navigating menus or building reports.
With AlisQI, you ask a question in plain language.
Which CAPAs are overdue?
Show complaints linked to product X.
Are deviations increasing on line 3?
The system interprets the question, retrieves the relevant records, and shows the results with traceable references.
Instead of operating the system, you query your operational data directly. The permissions and audit trail remain unchanged. What changes is how quickly you get from question to answer.
Quality systems rely on rules. When something happens, something else should follow.
Normally, setting up those rules requires technical knowledge.
With the Expression Engine Copilot, you simply describe what should happen.
If a test result is above specification, create a deviation and notify QA.
If the risk score is high, require an extra approval step.
The system converts your description into a working rule inside the workflow.
You decide the logic. The system handles the configuration.
Quality systems rely on rules. When something happens, something else should follow.
Normally, setting up those rules requires technical knowledge.
With the Expression Engine Copilot, you simply describe what should happen.
When a deviation or complaint is logged, the first question is often: have we seen this before?
AlisQI analyzes both the structured fields and the written description of the incident. While you create or review a record, the system suggests similar past cases.
You see how it was handled.
What the root cause was.
Which corrective actions were taken.
Instead of treating every issue as new, you build on what the organization has already learned.
Recurring problems become visible patterns. Decisions become more consistent. And over time, your quality system reflects accumulated experience, not isolated fixes.
Stop reading about AI. See it working.
- Form generation from a photo.
- COAs mapped without templates.
- Natural language access to your QMS.
See how it performs inside an operational quality system.