AI for spotting recurring supplier issues

At Syntalith, we propose an AI agent that compares new delivery records with complaints and supplier corrective work. The quality representative receives selected possible links with the original descriptions and dates. They decide whether to return to the earlier supplier discussion or handle the matter separately. This supports continuity after a complaint is closed and the team’s attention has moved to new deliveries.

A similar description after a packaging change

Suppose a company complained about crushed carton corners. The supplier described a packaging change, and quality completed the agreed work on that case. Later, the warehouse records “damage to package edges” on a new delivery. Another employee receives the report without knowing the earlier complaint.

The agent can propose a connection and prepare a short history: the previous complaint, the supplier’s recorded action, and the new warehouse observation. The employee checks whether the similarity matters and whether the records concern a comparable problem. Similar wording alone establishes neither a cause nor the failure of the earlier action.

If the employee confirms the relationship, they can use the history in a supplier conversation without first searching for the previous commitment. If the connection is wrong, they reject it and the new case retains its own description. The usefulness of the solution also depends on how many irrelevant suggestions people have to review.

Follow what happens after closure

An action register records who completed the task. Reviewing subsequent deliveries also requires finding the earlier case when a new description uses different language. An experienced quality representative may remember important cases, but a colleague covering for them needs access to that history.

Microsoft Dynamics 365 Supply Chain Management supports corrections associated with a nonconformance, assigned workers and planned dates, and completion or reopening of corrections. Use that workflow if it already serves the company. The proposed agent prepares material for deciding whether to revisit a case; it does not reopen one based on textual similarity.

If new reports use consistent codes that can easily be compared by supplier, a report in the existing system may suffice. An agent is more relevant when employees describe symptoms freely and comparison requires reading several accounts. Connecting the corrective action register supplies context by showing what the company and supplier already did in the earlier case.

Assessing the proposed scope

Syntalith can start with one supply area and agreed report sources. Your team identifies previous complaints and later observations. A quality representative can inspect the proposed connections: which lead to a useful history, and which merely connect similar words?

Include unrelated cases too, so evaluation is not limited to successful matches. The project scope should provide a convenient way to reject suggestions and continue work in the existing register. The team evaluates actual delivery observations; the absence of a new report does not itself establish that a problem has been permanently resolved.

Describe a situation where someone recognized a recurrence only during a supplier meeting. That is enough to begin identifying useful source connections. Discuss the scope through our AI agents service; collaboration details are on the pricing page.