Site queries returned generic links requiring manual searches. Now, an AI agent instantly delivers personalized schedules via backend API.
The second-largest city in Canada serves over 1.7 million citizens and manages a public website containing 40,000 pages of information that receives 50,000 daily visitors.
Citizens struggled to quickly find specific information, as inquiries about waste collection or public facilities only returned generic links...
“The idea of developing a virtual assistant for our citizens was already part of our responsible AI integration strategy and Microsoft Copilot Studio definitely helped accelerate that plan.”
Municipal government and public services provider for the city of Montreal.
Enterprise software, cloud infrastructure, and consumer electronics platform.
City of Montréal's Citizen support is part of this use case:
Related implementations across industries and use cases
New agents manually trawled complex file folders for answers. Now, they ask an AI assistant to instantly synthesize multi-source data.
Citizens navigated 40 siloed systems to access public services. Now, multilingual AI agents resolve routine queries on a single platform.
Citizens struggled to navigate complex city departments. Now, an AI answers routine queries, freeing staff for complex, face-to-face care.
New agents manually trawled complex file folders for answers. Now, they ask an AI assistant to instantly synthesize multi-source data.
Citizens struggled to navigate complex city departments. Now, an AI answers routine queries, freeing staff for complex, face-to-face care.
Staff manually cross-checked hundreds of pages. Agents now synthesize technical files to draft environmental analyses.
Staff reconciled spending line-by-line across scattered systems. Now, they use AI to automate the process and query data in plain English.
Basic troubleshooting consumed agents' time. Now, an AI fluent in local dialects independently resolves 73% of these cases.
Manual call evaluations delayed insights by weeks. Now, bots score calls at scale, empowering analysts to synthesize data in hours.
Site queries returned generic links requiring manual searches. Now, an AI agent instantly delivers personalized schedules via backend API.
The second-largest city in Canada serves over 1.7 million citizens and manages a public website containing 40,000 pages of information that receives 50,000 daily visitors.
Citizens struggled to quickly find specific information, as inquiries about waste collection or public facilities only returned generic links...
“The idea of developing a virtual assistant for our citizens was already part of our responsible AI integration strategy and Microsoft Copilot Studio definitely helped accelerate that plan.”
Municipal government and public services provider for the city of Montreal.
Enterprise software, cloud infrastructure, and consumer electronics platform.
City of Montréal's Citizen support is part of this use case:
Related implementations across industries and use cases
New agents manually trawled complex file folders for answers. Now, they ask an AI assistant to instantly synthesize multi-source data.
Citizens navigated 40 siloed systems to access public services. Now, multilingual AI agents resolve routine queries on a single platform.
Citizens struggled to navigate complex city departments. Now, an AI answers routine queries, freeing staff for complex, face-to-face care.
New agents manually trawled complex file folders for answers. Now, they ask an AI assistant to instantly synthesize multi-source data.
Citizens struggled to navigate complex city departments. Now, an AI answers routine queries, freeing staff for complex, face-to-face care.
Staff manually cross-checked hundreds of pages. Agents now synthesize technical files to draft environmental analyses.
Staff reconciled spending line-by-line across scattered systems. Now, they use AI to automate the process and query data in plain English.
Basic troubleshooting consumed agents' time. Now, an AI fluent in local dialects independently resolves 73% of these cases.
Manual call evaluations delayed insights by weeks. Now, bots score calls at scale, empowering analysts to synthesize data in hours.