From Document Approval to Release Readiness: Putting AI at the Quality Gate

We've all likely experienced finding the _FINAL (or _FINAL_REAL) version of a document and questioning if its' really the approved version. For manufacturers and other organizations managing controlled processes, that question can have significant consequences.

A product revision may depend on several related documents. A quality process may require a signed record before work can advance. A submitted document may be missing a required page or stamp. Everything can appear ready on the surface, but one overlooked detail holds the potential to create significant rework, delays, or compliance concerns downstream.

To determine whether all the appropriate conditions and approvals have been met, organizations need to understand what's there, evaluate whether information is ready, and act if anything is missing.

That's where an M-Files Quality and Release Readiness Agent can change the process.

The Cost of "Almost Ready"

Quality processes depend on precision.

Before something moves from one stage to another, employees may need to verify multiple pieces of information: Are all the required documents present? Does it contain the required stamp? Is anything missing?

Reviewing these relatively simple questions across hundreds or thousands of documents and processes, creates significant manual work. And the issue becomes more challenging when readiness depends on the relationships between documents.

Consider the following example: A bill of materials might have three required documents associated with it. All three documents exist, so at first glance the package appears complete. But only two have been approved. A process reviews document presence alone could allow work to move forward prematurely.

Meet the M-Files Quality and Release Readiness Agent

A Quality and Release Readiness Agent (a customized manufacturing M-Files Custom Agent) can serve as an intelligent review within a document-driven process, analyzing the relevant information at the point where a readiness decision needs to be made.

The agent can

• Determine whether required documents are present and in the appropriate approval state.
• Inspect content to determine whether a required signature or stamp is actually there
• Identify whether expected pages appear to be missing.

The purpose to answer the costly question "is this ready to move forward?". If the answer is yes, the workflow continues. If a required condition hasn't been met, the process flags a human to review the issue.

The process can be viewed through three stages.

1. Understand: First, the agent analyzes the documents and their context. What documents are associated with this process? What is their current state? Does a required element appear in the content? Is the information needed for the next step actually present? These distinctions matters because a document being uploaded doesn't mean the requirement behind were met.
2. Judge: Next, the agent applies the organization's predefined requirements. Perhaps three related documents must all reach an approved state before a revision can advance. Maybe a particular document requires a signature. Another process might require a stamp to appear on a submitted file. The agent evaluates what it finds against those defined conditions. Making these reviews repeatable help expedite processes and allows humans to focus on higher value work.
3. Act: Last the workflow responds to the judgment. If everything meets the requirements, work moves forward. If a signature is missing, the document can be routed back for attention. If another requirement isn't satisfied, the appropriate person can be notified.

With this custom agent, the quality check becomes part of the workflow rather than a manual task surrounding it, surfacing errors to the people equipped to solve them.

Putting AI Where the Decision Happens

Agentic quality processes need to understand relevant information, judge that information against defined requirements, and use the result to determine what happens next.

M-Files' context-first approach connects documents with the people, projects, and processes surrounding them. A quality record relates to a process. An approval relates to a release decision. That context creates an important foundation for bringing AI into document-heavy workflows and where M-Files Custom Agents move AI from the sidelines to where decision keep work moving - or stop it when it isn't ready.