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AI agent for police officers

Community Concern Follow-Up Agent

Every community concern tracked to an action and a measured result

AutomationGovernmentOperations
See how it worksGet access
Community Concern Follow-Up Agent: what goes in, what the agent does and what you get

What it does

Residents raise issues such as speeding, noise or drug activity at meetings and by phone, and they want to know something happened. This agent logs each concern and groups repeats by location and type. It pulls related call data for the area to see if the problem shows up in records. The officer chooses an action plan. After the action, the agent compares call data over equal before and after periods. If related calls did not drop, it brings the issue back for a new plan. When results improve, it drafts a short update for residents, and the officer approves anything public. Named individuals never appear in updates. Edge case: concerns naming a specific person are logged for the officer but never turned into a public update.

How it works

Follow the arrows from top to bottom. The orange dashed arrow is the loop: when a check fails, the agent goes back and tries again.

Start and resultWhat it doesA check on its own workWaits for your OKGoes back and retries
ApprovedYes, continueApprovedNo 1 STARTS WHEN New concern logged 2 DOES Group with similar concerns by location and type 3 USES A TOOL Pull related call data for the area 4 YOU APPROVE Officer chooses an action plan 5 USES A TOOL Compare call data before and after the action 6 CHECKS THE RESULT Did related calls drop? If not: bring the issue back for a new plan. Back tostep 4. 7 USES A TOOL Draft a short update for residents 8 YOU APPROVE Officer approves the public update 9 RESULT Concern closed with result
Read the steps as a list
  1. New concern logged
  2. Group with similar concerns by location and type
  3. Pull related call data for the area
  4. Officer chooses an action planThe agent waits here for your OK.
  5. Compare call data before and after the action
  6. Did related calls drop?If not: bring the issue back for a new plan. Back to step 4.
  7. Draft a short update for residents
  8. Officer approves the public updateThe agent waits here for your OK.
  9. Concern closed with result

How it decides

Repeat concerns at the same place become one issue. Improvement means fewer related calls over the same length of time.

  • Same location and type group together
  • Measure over equal before and after periods
  • Named individuals never appear in updates

Make it yours

Every agent is a starting point. You choose these settings for your own situation.

  • Measurement period (default 30 days)
  • Concern categories
  • Update channel (newsletter, meeting, social)
  • Grouping distance

What keeps you in control

It always asks you first

  • Officer chooses actions
  • Officer approves public updates

Hard limits

  • Never posts publicly
  • No personal data in updates

It stops when

  • Done: concern resolved
  • Stop: concern referred to another agency

Set it up

We guide you through the set-up, step by step

Members get the full set-up guide for this agent. No technical skills needed: you copy, paste and upload.

10 minto set it up in your AI
5 AIsChatGPT, Claude, Copilot, Gemini, Grok
  • One set of instructions to paste into your AI, with the clicks for ChatGPT, Claude, Microsoft 365 Copilot, Gemini and Grok
  • The agent then walks you through connecting your own data, one source at a time
  • A downloadable copy with the flow chart, the rules and the full guide
Get access to this agent

An example run

What happensFive residents reported speeding on Elm Street, and calls showed 9 traffic complaints in 30 days. After two weeks of extra patrol, complaints ran at 7 in 30 days, so the check failed and the issue went back for a new plan. The officer requested a city speed trailer. The next period showed 2 complaints, and the officer approved the agent's update for the neighborhood group.

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