Product Experience
Every role. One platform.
From front-counter staff handling resident requests to the CAO reviewing council-ready reports — every role has a purpose-built journey. Explore how Civic Work Order / 311 works for your team.
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See Civic Work Order / 311 handle a complete resident service request — from intake through resolution and council reporting.
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Explore the Interface
Click through the actual Civic Work Order / 311 interface. Navigate between the dashboard, resident profiles, service requests, and reports to see how everything connects.
127
Open Requests
-18% vs last month2.1d
Avg Resolution
-30% vs last month92%
SLA Compliance
+14% vs last month84%
Satisfaction
+9% vs last monthRecent Activity
Pothole repair completed — before/after photos uploaded
Roads · 2 min ago
Water main break reported — emergency dispatch triggered
Water · 5 min ago
Streetlight outage assigned to Crew 4 via mobile
Streetlights · 12 min ago
Graffiti removal work order scheduled for tomorrow
Parks · 18 min ago
IoT sensor: smart waste bin overflow alert — auto work order
Waste · 25 min ago
Role-Based Journeys
One Platform, Every Perspective
Select a role to explore their complete journey through Civic CRM — from day-one onboarding to daily workflows and strategic outcomes.
Customer Service Rep
From Citizen Call to Case Creation
Follow the complete lifecycle of a 311 service request — from multi-channel intake through intelligent categorization, duplicate detection, and dispatch to the correct department. Zero lost requests, instant acknowledgement, and full audit compliance.
Receive
Request arrives
Any channel — 311 phone, web portal, mobile app, email, social media, walk-in, AI chatbot, or IoT sensor — captured and timestamped automatically with channel source, geographic metadata, and photo attachments.
The multi-channel intake system captures service requests from all municipal channels in real-time. Phone calls use call centre scripts with address lookup. Portal and mobile submissions include map pin drop with GPS auto-location. Email auto-parsing creates cases from inbound messages. The AI chatbot (spec 7.1) handles routine requests end-to-end with seamless escalation. IoT sensors auto-generate work orders with diagnostic data. Every request receives a unique reference number (WO-YYYY-NNNNN).
Categorize
AI-assisted classification
The intelligent categorization engine suggests the most likely request category based on description keywords, location context, and uploaded photos. Computer vision analyzes images to identify issue type and estimate severity.
As the resident describes their issue, the AI suggests categories from the configurable service catalog (spec 1.2): roads, water, sewer, waste, parks, streetlights, traffic, bylaws. Computer vision photo analysis (spec 7.3) identifies the issue type and estimates severity — pothole depth, graffiti coverage area, damage extent. Auto-populated required fields based on category. Location-based suggestions flag potential duplicates near active work orders.
Locate
GIS-powered positioning
Capture precise location via address search, map pin drop, GPS, or intersection. Address validated against municipal GIS data. Auto-link to the nearest municipal asset (road segment, hydrant, streetlight). Ward auto-assigned for routing and reporting.
The geolocation engine (spec 1.4) validates addresses against the municipal GIS parcel database. GPS coordinates from mobile submissions are verified against photo EXIF data. The asset linker identifies the nearest relevant asset — which road segment, which water main, which streetlight. Ward and neighbourhood auto-assignment enables councillor-level routing and reporting. All location data feeds the community issue map and heat map analytics.
Deduplicate
GIS proximity check
GIS proximity matching checks for existing open requests at the same or nearby location for the same issue type. Potential duplicates are presented for linking. Linked requests ensure all requestors are notified upon resolution.
The duplicate detection engine (spec 1.6) performs spatial proximity matching — checking for open requests within a configurable radius for the same issue type. Staff see potential matches with distance and similarity scoring. Linked duplicate requests maintain separate requestor records but reference a single work order. Duplicate count tracks the 'heat' of an issue — 10 complaints about the same pothole auto-escalate to high priority. All requestors receive resolution notifications.
Route
Smart dispatch
The routing engine evaluates request type, location, asset ownership, priority, and SLA targets to assign the request to the correct department. Emergency requests trigger immediate dispatch. Standard requests enter the priority queue.
The smart router (spec 2.2) evaluates configurable rules matching request type, location (ward, service area), asset ownership, and priority classification. Emergency requests (water main break, road hazard) bypass normal routing and trigger immediate dispatch to available crews via push notification. Standard requests are prioritized and queued for supervisor review or auto-assignment. Escalation routing activates if not acknowledged within configured hours. Every routing decision is logged.
Acknowledge
Instant confirmation
Automated acknowledgement sent to the resident via their preferred channel (email, SMS, portal) with request reference number, category, expected SLA timeline, and assigned department. Confirmation delivered in under 1 hour.
The notification engine (spec 5.1) sends an automated acknowledgement immediately upon request creation via the resident's preferred channel. The confirmation includes the unique reference number (WO-YYYY-NNNNN), request category, priority classification, expected resolution timeline based on SLA targets, and assigned department. Bilingual (en/fr) templates with resident language preference detection. Acknowledgement delivery tracked — under 1 hour target vs. 24-hour baseline.
Intake Journey
0 / 6
Step 01
Receive
Request arrives
Any channel — 311 phone, web portal, mobile app, email, social media, walk-in, AI chatbot, or IoT sensor — captured and timestamped automatically with channel source, geographic metadata, and photo attachments.
The multi-channel intake system captures service requests from all municipal channels in real-time. Phone calls use call centre scripts with address lookup. Portal and mobile submissions include map pin drop with GPS auto-location. Email auto-parsing creates cases from inbound messages. The AI chatbot (spec 7.1) handles routine requests end-to-end with seamless escalation. IoT sensors auto-generate work orders with diagnostic data. Every request receives a unique reference number (WO-YYYY-NNNNN).
Step 02
Categorize
AI-assisted classification
The intelligent categorization engine suggests the most likely request category based on description keywords, location context, and uploaded photos. Computer vision analyzes images to identify issue type and estimate severity.
As the resident describes their issue, the AI suggests categories from the configurable service catalog (spec 1.2): roads, water, sewer, waste, parks, streetlights, traffic, bylaws. Computer vision photo analysis (spec 7.3) identifies the issue type and estimates severity — pothole depth, graffiti coverage area, damage extent. Auto-populated required fields based on category. Location-based suggestions flag potential duplicates near active work orders.
Step 03
Locate
GIS-powered positioning
Capture precise location via address search, map pin drop, GPS, or intersection. Address validated against municipal GIS data. Auto-link to the nearest municipal asset (road segment, hydrant, streetlight). Ward auto-assigned for routing and reporting.
The geolocation engine (spec 1.4) validates addresses against the municipal GIS parcel database. GPS coordinates from mobile submissions are verified against photo EXIF data. The asset linker identifies the nearest relevant asset — which road segment, which water main, which streetlight. Ward and neighbourhood auto-assignment enables councillor-level routing and reporting. All location data feeds the community issue map and heat map analytics.
Step 04
Deduplicate
GIS proximity check
GIS proximity matching checks for existing open requests at the same or nearby location for the same issue type. Potential duplicates are presented for linking. Linked requests ensure all requestors are notified upon resolution.
The duplicate detection engine (spec 1.6) performs spatial proximity matching — checking for open requests within a configurable radius for the same issue type. Staff see potential matches with distance and similarity scoring. Linked duplicate requests maintain separate requestor records but reference a single work order. Duplicate count tracks the 'heat' of an issue — 10 complaints about the same pothole auto-escalate to high priority. All requestors receive resolution notifications.
Step 05
Route
Smart dispatch
The routing engine evaluates request type, location, asset ownership, priority, and SLA targets to assign the request to the correct department. Emergency requests trigger immediate dispatch. Standard requests enter the priority queue.
The smart router (spec 2.2) evaluates configurable rules matching request type, location (ward, service area), asset ownership, and priority classification. Emergency requests (water main break, road hazard) bypass normal routing and trigger immediate dispatch to available crews via push notification. Standard requests are prioritized and queued for supervisor review or auto-assignment. Escalation routing activates if not acknowledged within configured hours. Every routing decision is logged.
Step 06
Acknowledge
Instant confirmation
Automated acknowledgement sent to the resident via their preferred channel (email, SMS, portal) with request reference number, category, expected SLA timeline, and assigned department. Confirmation delivered in under 1 hour.
The notification engine (spec 5.1) sends an automated acknowledgement immediately upon request creation via the resident's preferred channel. The confirmation includes the unique reference number (WO-YYYY-NNNNN), request category, priority classification, expected resolution timeline based on SLA targets, and assigned department. Bilingual (en/fr) templates with resident language preference detection. Acknowledgement delivery tracked — under 1 hour target vs. 24-hour baseline.
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