Reported impact
Business outcome
Localiza reduced 8.3 working hours per employee per month, improved inclusivity, and increased productivity in key areas of the company.
- Customer Experience
- Productivity Improvement
- Scalability
MicrosoftTravel and HospitalityIT Operations AutomationContact CenterGenerative AI / LLMCustomer ExperienceProductivity ImprovementScalability2024 MicrosoftMS#0078d4Travel and HospitalityBrazilLocaliza needed to increase employee productivity and optimize repetitive manual tasks.Denys Damm, End-User Experience Lead in Information Technology, Localiza Localiza&Co is a leader in the…Dec 3, 20245IT Operations AutomationMicrosoft 365 Copilot · Microsoft Copilot Studio0 2024-12-03 5
Localiza
IT Operations Automation
Localiza needed to increase employee productivity and optimize repetitive manual tasks.
Denys Damm, End-User Experience Lead in Information Technology, Localiza Localiza&Co is a leader in the mobility industry in Latin America, with over 700 branches across seven countries: Brazil, Argentina, Colombia, Ecuador, Mexico, Paraguay, and Uruguay.
Solution
Localiza built its Microsoft solution to improve employee-productivity and operational workflows. Localiza needed to increase employee productivity and optimize repetitive manual tasks. Key components included Microsoft 365 Copilot delivered dashboards, apps, or copilots to users, and Microsoft Copilot Studio coordinated workflows, prompts, or deployment. User prompts and domain content are orchestrated through Microsoft Copilot Studio, processed by Microsoft Copilot Studio, and then delivered through Microsoft 365 Copilot so Localiza can return context-aware answers or automation in the flow of work. The governed Microsoft stack gave Localiza a reusable foundation for generative ai / llm, contact center while keeping deployment, security, and day-to-day operations inside the Microsoft estate. Localiza reduced 8.3 working hours per employee per month, improved inclusivity, and increased productivity in key areas of the company.
Data flow
User prompts and domain content are orchestrated through Microsoft Copilot Studio, processed by Microsoft Copilot Studio, and then delivered through Microsoft 365 Copilot so Localiza can return context-aware answers or automation in the flow of work.
Solution architecture
- Serving
- Microsoft 365 Copilot Provides embedded generative-AI assistance inside everyday employee productivity workflows.
- Orchestration
- Microsoft Copilot Studio Provides the managed environment to design, test, and operate custom copilots.
Architecture clues
- Denys Damm, End-User Experience Lead in Information Technology, Localiza Localiza&Co is a leader in the mobility industry in Latin America, with over 700 branches across seven countries: Brazil, Argentina, Colombia, Ecuador, Mexico, Paraguay, and Uruguay.
- The company has observed a significant improvement in employee and team productivity when using Copilot to create dashboards for Microsoft Viva Insights .
Evidence from the source
Denys Damm, End-User Experience Lead in Information Technology, Localiza Localiza&Co is a leader in the mobility industry in Latin America, with over 700 branches across seven countries: Brazil, Argentina, Colombia, Ecuador, Mexico, Paraguay, and Uruguay.
Localiza needed to increase employee productivity and optimize repetitive manual tasks.
Localiza reduced 8.3 working hours per employee per month, improved inclusivity, and increased productivity in key areas of the company.
Microsoft 365 Copilot: Enhancing internal productivity The decision to adopt Microsoft 365 Copilot was driven by the need to innovate and improve employee productivity and efficiency.
Recently, Localiza&Co embarked on a digital transformation journey centered on generative AI by implementing Microsoft 365 Copilot , an AI tool that is revolutionizing the way the company operates and delivers value.
The company implemented Microsoft 365 Copilot and integrated AI to automate processes and improve efficiency.
Transparency Evidence & methodology
Review how this reference was scored and trace each normalized claim back to its documented source.
Scoring methodology
How scores are calculated
Customer Reference Value measures usefulness as a customer reference. Evidence Confidence measures the quality and traceability of available evidence, not independent verification.
Customer reference value57/100
- Problem clarity12/20Measures whether the customer's operational problem is specific enough to compare.
- Implementation depth20/25Rewards named components, data flow, integrations, and architecture detail.
- Outcome specificity20/20Measures whether the reported benefit is concrete rather than a generic claim.
- Quantified impact0/250 metrics describe measurable impact.
- Deployment scale5/10Rewards evidence of a live or scaled deployment and meaningful integration scope.
Evidence confidence87%
- Source authority20/25The main evidence is an official vendor-published customer story.
- Claim traceability21/2510 of 12 key fields link to a named source.
- Direct evidence20/206 direct source quotes retained.
- Date provenance10/10The publication date comes from the source page or publisher.
- Source transparency8/101 source reference document publisher, URL, authority, retrieval, and supported fields.
- Implementation specificity8/10Rewards source-backed components, data flow, quantified impact, and a specific outcome.
Traceability
Sources & provenance
Field coverage shows which facts each source supports. Dates are shown only when documented by the source.
- https://www.microsoft.com/en/customers/story/19818-localiza-microsoft-365-copilotMicrosoftFirst-party
Localiza customer story
Supports- Customer
- Business problem
- Solution
- Products
- Solution components
- Data flow
- Integrations
- technical area
- use case category
- Business outcome
- outcome category
- Metrics
- Architecture
- evidence quotes
- Publication date
Date evidence
- Published on source page Dec 3, 2024 · Microsoft · First-partyOpen date source
Not separately sourced Industry, Region, Company size. Treat these normalized attributes as lower-confidence until a dedicated source is added.
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