Filling Checklist metadata with AI

Filling Checklist metadata with AI allows teams to automate the process of capturing and entering structured data into checklists. Instead of manually reading through documents, conversations, or emails to fill out checklist fields, Unifize AI extracts the relevant information and pre-fills the data directly into the record. This capability reduces manual effort, minimizes errors, and accelerates process execution.

How it works

AI reads unstructured data from emails, conversations, and attached documents in a record. It then intelligently populates the required checklist fields, like product details, reasons for issues, quantities, corrective actions, or root cause analysis, based on the content provided.

This feature enables teams to move faster from data capture to decision-making, ensuring accurate and compliant record-keeping throughout quality, compliance, and operational processes.

Process steps

Step 1: Initiate a record

• You can import your email data by forwarding any email into Unifize.

• A new process will be created upon doing the same. Your email will be visible in the conversation window of the new process. You can click on the "Fill Checklist based on email" button for the AI to start parsing your email.

Step 2: AI extracts and fills Checklist data

• AI scans the record’s conversation, attached documents, or email body.

• With a single click, AI automatically fills in checklist fields like:

  • Product Name

  • Product Number

  • Product Quantity

  • Reason for Complaint

  • Root Cause Analysis

  • Corrective Actions

  • Date of Report

Step 3: Review and confirm

• Users review the AI-generated suggestions.

• Suggestions are editable before being saved to ensure accuracy and alignment with process requirements.

Step 4: Take action

• Once the checklist is filled, users can assign dispositions, initiate investigations, or start root cause analysis directly from the same record.

• For example, AI can guide users through the 5-Why methodology to quickly identify the root cause.

Step 5: Execute Corrective Actions

• Based on the identified root cause, AI proposes corrective actions.

• Users can select, assign owners, and set due dates—keeping the entire workflow within one collaborative workspace.

Step 6: Manage related processes

• If a corrective action involves a document update, users can launch a Change Request directly from the record.

• AI evaluates the change impact and identifies associated risks.

Step 7: Update training automatically

• Once the change is approved, AI generates updated training materials.

• Employees automatically receive notifications about the new training, ensuring up-to-date compliance and knowledge retention.

Best Practices

• Forward detailed and clear emails or attach comprehensive documents for the most accurate AI results.

• Pair AI-driven checklist filling with Configurable AI Prompts for highly tailored outputs.

• Review AI suggestions thoroughly before finalizing, especially for compliance-critical processes.

• Use AI consistently in complaint handling, CAPAs, audits, or supplier quality processes to reduce cycle time.