From findings to better QMS—guided by AI, controlled by governance
PEDCO AuditPro will turn audit recommendations into concrete, multi-step QMS improvements with an interactive change workflow—combining AI-assisted drafting with approvals, audit trails, and safe rollout.
Why it matters
Finding issues is only half the work. The real challenge is translating findings into consistent, high-quality QMS updates—without creating new inconsistencies, breaking references, or losing governance control.
Interactive AI-Supported QMS Improvement will compress time-to-fix while improving quality and traceability of changes across sites and languages.
AI-guided improvement in action
From agent-proposed changes to approved rollout—full transparency at every step
What this capability will deliver
AI-generated change plans you can control
- An agent proposes a multi-step change plan based on your audit findings and QMS structure
- Users can reorder, edit, or extend steps before execution
- Effort and impact guidance to support prioritization
Side-by-side improvements with full transparency
- A diff-style editor shows current vs. proposed text
- Per-change Accept / Reject controls with rationale
- Tooltips that link changes back to the original findings and evidence
Safe execution with built-in checks
- "Run Plan" applies updates safely (branching by default)
- Automated checks for terminology consistency, reference integrity, and contradiction risk
- Optional "what-if" preview to understand downstream impact before rollout
Governance and auditability by design
- Assign reviewers and capture approvals (including e-signature patterns if needed)
- Immutable audit trail of who changed what, when, and why
- Rollback support and phased rollout across sites and languages
Learns over time (organization memory)
- Capture overrides, preferred terminology, and patterns
- Reduce future edits and keep improvements aligned with local doctrine
Where it fits in the platform
This module builds on other PEDCO AuditPro capabilities:
Compliance Audits & Templates
What needs to change
Evidence Mapping & Traceability
Why it needs to change
QMS Content Quality & Consistency
How to keep content clean post-change
UI + MCP
Integrated, not separate
UI: guided improvement workflow
- Change plan builder, review queues, and controlled editing
- Side-by-side diffs with accept/reject and rationale capture
- Governance workflow with approvals and audit trails
MCP: expose improvement agent to AI tools
- Model Context Protocol (MCP) server for agent-driven change plans
- Let external AI assistants propose and track QMS improvements
- Sync approvals and rollout status with chat interfaces and automation workflows
Typical use cases
Fix recurring nonconformities
With standardized change patterns
Harmonize multi-site QMS content
While preserving local variants
Accelerate change control
With defensible review and approval workflows
Improve quality at scale
While minimizing new contradictions and drift
Outputs you get
A structured change plan linked to findings and evidence
Proposed edits with accept/reject decisions and rationales
Approval records and immutable audit trail
Rollout status across sites, repositories, and languages