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The Angeiras coastline, in Lavra
Type
Case study
Client
Lavra Parish Council
Published

In Lavra,
every issue reaches the team already categorized

Lavra Parish Council uses AI to categorize every report, merge duplicates and work out who should resolve it. Manual triage disappears, and that is where the biggest return lies.

Triage is the step all of a parish's work depends on. Before any team heads out, someone has to work out what happened, where, how urgent it is, and whether it belongs to the parish, the municipality or another entity.

Potholes, overflowing bins, broken street lights: the same fault arrives several times, from different people and through different channels. It is the most repetitive work there is, and the work that takes the most time from resolution.

How it works

Every report enters a single flow, with text, photos and location, wherever it comes from.

AI reads the text and images, identifies the problem, extracts the location and proposes a category and priority.

Repeat reports about the same problem become one case.

Location and competence rules show who is responsible.

The parish team receives the prepared case, checks it and decides.

Each validated issue becomes a task with an owner and a deadline. Its status, the record of the intervention and proof of the work stay linked to the original report.

One street light,
from report to resolution

Three residents report a street light that is out: one by email, one through a form, a third with a photo.

AI recognizes the same problem in all three messages, proposes the street lighting category and extracts the location. The three reports become one case.

Competence rules point to the responsible entity. The team opens the prepared case and only has to confirm it.

From there, the task has an owner and a deadline, and anyone on the team can see where it stands. When the light comes back on, proof of the intervention stays with that issue.

Where the return is

Reading, classifying, merging and routing stop being manual work. The time moves to fixing the parish's problems.

The return grows with volume: the more reports arrive, the more work categorization avoids.

Every decision stays with the team, which now decides with the case prepared and the full history in view.

The same technology fits any organisation that receives requests in quantity and has to route them to the right person.

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