Municipal AI Service Request Logs

This dataset provides detailed logs of municipal service requests managed by AI-driven systems, including operational metrics, routing decisions, resolution times, and citizen feedback. It enables smart city teams to benchmark digital transformation, optimize workflows, and enhance citizen engagement by analyzing automated service delivery outcomes and identifying process bottlenecks.

  • last updated 19 Jan 2026
  • by GoMask
The brief that made it

Benchmarking and optimizing municipal digital transformation initiatives

Sample rows

preview · 8 of 132 rows · all 20 columns
request_idstringpriority_levelstringai_confidence_scorefloatescalated_to_humanbooleanservice_location_citystringcitizen_idstringrequest_typestringsubmission_datetimedatetimeai_routing_decisionstringassigned_teamstringstatusstringresolution_datetimedatetimeresolution_time_hoursfloatcitizen_feedback_scoreintegercitizen_feedback_commentsstringservice_location_streetstringservice_location_statestringservice_location_postal_codestringservice_location_countrystringrequest_descriptionstring
REQ-000001urgent0.95trueChicagoCITZ-ALPHA-101pothole_repair2024-06-03T09:14:00ZPublic Works Department - Pothole TeamRoad Crew Aresolved2024-06-03T13:41:00Z4.455Quick service, thank you!155 Main StIL60617USLarge pothole near intersection needs urgent fixing.
REQ-000002medium0.78falseLos AngelesCITZ-BETA-209waste_collection2024-06-02T08:10:00ZSanitation Services - Waste PickupWaste Collection Team Northin_progressblankblankblankblank234 Oak AveCA90012USMissed waste pickup on scheduled day.
REQ-000003high0.87trueSpringfieldCITZ-GAMMA-302street_light_issue2024-06-01T22:33:00ZInfrastructure Division - Lighting UnitLighting Repair Team Westclosed2024-06-02T03:15:00Z4.74Resolved after reporting, thanks.87 Elm StMA01108USStreet light flickers and doesn't stay on.
REQ-000004medium0.79falseBuffaloCITZ-DELTA-412graffiti_removal2024-06-04T07:49:00ZCommunity Services - Parks Clean UpPark Maintenance Teamopenblankblankblankblank310 Maple DrNY14201USGraffiti on public park wall.
REQ-000005high0.84trueNew YorkCITZ-EPSILON-511noise_complaint2024-06-03T23:51:00ZCompliance Office - Noise EnforcementNoise Compliance Teamresolved2024-06-04T07:10:00Z7.323Issue resolved, but took longer than expected.56 River RdNY10032USConstant loud music at night from nearby apartment.
REQ-000006medium0.62falseSan DiegoCITZ-ZETA-613other2024-06-01T12:25:00ZPublic Works Department - Sidewalk RepairSidewalk Crewopenblankblankblankblank210 Forest LnCA92101USRequesting sidewalk repair due to cracks.
REQ-000007low0.48falseAtlantaCITZ-THETA-701waste_collection2024-06-02T14:18:00ZSanitation Services - Public WasteWaste Collection Team Centralin_progressblankblankblankblank92 5th AveGA30303USOverflowing public trash bin at bus stop.
REQ-000008high0.91falseRivertonCITZ-IOTA-802pothole_repair2024-06-03T16:37:00ZPublic Works Department - Pothole TeamRoad Crew Bclosed2024-06-04T08:10:00Z15.554Prompt fix, good job.333 School StUT84065USSmall pothole near school entrance.

What the 132 rows show

from the 132-row sample

Low (priority level) stands out: mean ai_confidence_score is 0.42, against 0.80 for the rest.

  • 29%escalated_to_human = true
  • 0.79median ai_confidence_score
  • 3service location countries
  • 4statuses
  • 6request types
  • 21service location states
Mean ai_confidence_score by priority_level132 rows
00.510.42low13 rows0.68medium48 rows0.84high46 rows0.94urgent25 rows
ai_confidence_score132 rows, in bands of 0.1
0204024510182839260.20.61ai_confidence_score →

Median 0.79, from 0.27 to 0.99.

service_location_city132 rows · top 10 of 30 values
  1. Buffalo13
  2. Chicago11
  3. Los Angeles9
  4. San Francisco8
  5. Toronto8
  6. Seattle7
  7. Boston7
  8. Dallas7
  9. Denver6
  10. London6
20 columns by typefrom the column list below
  • string 14
  • integer 1
  • float 2
  • datetime 2
  • boolean 1

Columns

20 columns in four groups
blueprint · 20 columns
columntypedescriptionexample
Text 14 columns
request_idstringUnique identifier for the service requestuniqueREQ-000001
citizen_idstringAnonymized identifier for the citizen submitting the requestCITZ-ALPHA-101
request_typestringType of municipal service requested (e.g., pothole repair, waste collection)6 valuespothole_repair
request_descriptionstringDetailed description of the issue or request provided by the citizenoptionalLarge pothole near inters…
ai_routing_decisionstringAI system's routing decision (e.g., assigned department/team)Parks Department Routing
assigned_teamstringName of the municipal team assigned to resolve the requestRoad Crew A
priority_levelstringPriority level assigned by AI (e.g., low, medium, high, urgent)low · medium · high · urgenturgent
statusstringCurrent status of the request (e.g., open, in_progress, resolved, closed, rejected)open · in_progress · resolved · closed · rejectedresolved
citizen_feedback_commentsstringOptional comments provided by the citizen after resolutionoptionalPrompt fix, good job.
service_location_streetstringStreet address where the service is neededoptional155 Main St
service_location_citystringCity of the service locationChicago
service_location_statestringState of the service locationIL
service_location_postal_codestringPostal code of the service location60617
service_location_countrystringCountry of the service location3 countriesUS
Numbers 3 columns
resolution_time_hoursfloatTotal time taken to resolve the request, in hours0 or more · optional4.45
citizen_feedback_scoreintegerCitizen's feedback rating after resolution (1-5 scale)1 to 5 · optional5
ai_confidence_scorefloatAI system's confidence score in routing decision (0-1 scale)0 to 1 · optional0.95
Dates and times 2 columns
submission_datetimedatetimeTimestamp when the request was submitted2024-06-03T09:14:00Z
resolution_datetimedatetimeTimestamp when the request was resolved (if applicable)optional2024-06-03T13:41:00Z
True or false 1 column
escalated_to_humanbooleanIndicates if the request was escalated from AI to a human operatortrue

Use it for

  • escalated to h…29%38 of 132 rowsmean ai confidence sc…0.42low0.68medi…0.84high0.94urge…

    A government dashboard

    The escalated_to_human rate, ai_confidence_score by priority_level and a breakdown of service_location_city. Excel, Power BI or Tableau.

  • Why do the 13 low rows have a mean ai_confidence_score of 0.42?

    A root-cause class exercise

    Hand out the rows and one question. The answer is in the data, not in the brief.

  • A software demo

    Believable requests with citizen_id, request_type and request_description to fill a screen in front of a buyer.

Not quite right?

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This dataset132 rows20 columns
Yours10,000 rows20 columnsservice_location_street: UK only

blueprint · municipal-ai-service-request-logs

Behind this dataset

Same schema. As many rows as you need.

These 132 rows came out of a blueprint — 20 columns with generation rules behind each one. Open it in Data Factory to retune a column, add your own, wire in foreign keys, and run it at the size you actually need.

Rules it was built with
  • Each row represents a unique citizen service request
  • Requests are assigned to departments via AI algorithm
  • Include timestamps for request creation, assignment, and resolution
  • Log automated vs manual routing decisions
  • Track outcome: resolved, pending, or escalated
  • Capture feedback rating if available
Rows
Open the blueprint in Data Factory

1 credit per row. New accounts start with 25 free credits.

Exports
CSV, JSON, JSONL, Parquet, SQL, Excel, TSV, XML
Licence
yours to use, including commercially
API slug
municipal-ai-service-request-logs

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