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descriptive
OneService lets Singapore residents report municipal issues — littering, pests, faulty facilities, illegal parking — via photo and location
Permanent project revision
Revision 2026-10-05-baseline · effective 2026-10-05
Current revision. This is the snapshot used by the live entity page.
Created the first structured Evidence Passport with 10 claims and 5 source dossiers.
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add /evidencePassport — Added claim-level evidence mapping and source dossiers.add /revisionHistory — Established a permanent, hash-addressed baseline revision.The text below is copied verbatim from the published record. Each claim names the source dossiers that carry it; caveats stay attached to the claim they qualify.
clm-ad760b88278c5844
descriptive
OneService lets Singapore residents report municipal issues — littering, pests, faulty facilities, illegal parking — via photo and location
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without identifying which government agency or town council is responsible; the app routes each case automatically
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Live since January 2015
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it added an AI chatbot on WhatsApp and Telegram in 2021
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in 2026 a voice-message beta, Tell Us @ OneService, is being trialled on both
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After the Municipal Services Office linked the feedback systems of 11 agencies and 16 town councils
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the average time to close 90% of complex multi-agency cases fell from 16 working days at end-2015 to 11 by end-2017 (MSO figures, reported by the Centre for Liveable Cities)
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an analysis tying stray-dog complaints to construction sites prompted the veterinary authority and HDB to trap dogs around site clearance
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what shortened multi-agency cases was a back-end system that tracks every case across agencies and alerts any agency that has not accepted one within five working days
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A reporting app without that shared tracking only moves the question of who is responsible from the resident to the officer
This layer records what is known about each source, what is still missing, and the exact snapshot this page is rendering. A missing date, archive or hash stays visible as missing.
Awaiting operator and domain-expert review; publication of this revision implies neither.
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src-8b174689d9c47e07Official launch announcement: date, initial agencies, features
src-ab67d29edf773119Case study on the backend integrated case-management system and MSO's role
src-07063b064677af26Current partner count (10 agencies, 17 town councils), chatbot channels, current app features
src-520c2549b3c4843915 July 2021 launch of the AI/NLP-based WhatsApp and Telegram chatbot
src-376777d82f7293f7GovTech's account of building the chatbot: a case-type categoriser, a case-details recogniser at 85 per cent accuracy, and routing cases to the right agency 85% of the time.