Principle
Minimum necessary model context
TabPro AI is designed to send only non-identifiable data to AI models as part of the workflow, not broad raw project context that is unrelated to the task.
Security
Security starts with controlled data flow and human review.
Buyers do not need vague AI promises. They need to understand what data moves through the product, how reviewers stay in control, and how the workflow avoids turning project information into another unmanaged spreadsheet chain.
Current posture
The core security story should stay concrete.
This page is intentionally focused on operating principles you can explain clearly today, without overpromising formal certifications or controls that are still evolving.
Principle
Human-reviewed outputs
The product is built around reviewer confirmation. Extracted data can be checked against the source drawing before it moves into downstream workflows.
Principle
Source-linked traceability
Reviewers can connect extracted records back to the drawing context they came from, which improves QA and reduces blind acceptance of machine output.
Principle
Workflow continuity
Keeping one reviewed dataset reduces copy-paste handoffs and spreadsheet sprawl, which also reduces data handling risk across the job lifecycle.
Data handling
A simple story buyers can evaluate quickly
The strongest version of your security page is operationally honest. Explain what the product does today, what gets reviewed by humans, and which questions should be covered in a live security conversation.
Workflow visibility
Processing is visible, not hidden behind a black box.
Topics we should review with buyers
AI model usage and what data is sent during processing
How reviewers validate extracted equipment before downstream use
Project data flow from upload through setup and reporting
Operational questions your team wants answered before rollout
Need more detail?
Bring your security questionnaire into the live review.
Security questions are best handled in context, alongside the actual workflow. That keeps the conversation grounded in how the product processes drawings, what reviewers approve, and where data moves next.