AWS Commercial and Professional Services Global

Accenture Brazil

Customer Service Automation · Security and Compliance · System Migration

Call center management wanted to scale services to not only align with the company’s growth, but to expand its services to clients who wanted to outsource their service desk operations with Accenture. However, Accenture Brazil’s call center operations required major investments in on-premises infrastructure, preventing it from gaining the agility and cost effectiveness it needed to grow.

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25,000 calls per month in three languages

50% in infrastructure costs saving using a cloud-based contact center

As a result, Accenture Brazil has already cut its infrastructure costs by 50 percent or more, with the potential for even bigger cost savings in the future.

The company has reduced its infrastructure costs by 50 percent and can scale call center resources up or down instantly.

Reported impact

Business outcome

Completing its migration to Connect Customer yielded a simpler and leaner infrastructure, freeing up resources to further innovate on services. "We can scale our infrastructure resources up or down, quickly and with very little effort, while paying only for the services that we're using," Salomão said. As a result, Accenture Brazil has already cut its infrastructure costs by 50 percent or more, with the potential for even bigger cost savings in the future.

Solution

Accenture Brazil is part of a global management consulting, technology services, and outsourcing company, helping clients become high-performance businesses. It faced challenges with its inflexible and costly on-premises service desk infrastructure for employees, which was serving more than 17,000 staff members in Latin America. How Accenture Brazil leveraged Amazon Connect Customer for operational efficiency, cost reduction, and technological innovation With Amazon Lex and Amazon Polly , the company implements multi-lingual chatbots and automated voice systems required for call-based self-service offerings. The center’s newfound flexibility, cost effectiveness, and scalability gives Accenture Brazil room to take customer service to the next level, with plans to expand use cases for ML and generative AI with Amazon Bedrock Amazon SageMaker Connect Customer reduced our operational costs and gave us greater flexibility. After a complete migration

Data flow

processing runs on Amazon Bedrock, Amazon SageMaker; and outputs are exposed through Amazon Polly for the chatbot analytics workload.

Solution architecture

3 components · 2 layers

Compute
- Amazon Bedrock Runs core compute or model execution for the chatbot analytics workload.
- Amazon SageMaker Runs core compute or model execution for the chatbot analytics workload.
Serving
- Amazon Polly Runs core compute or model execution for the chatbot analytics workload.

Evidence from the source

"Connect Customer reduced our operational costs and gave us greater flexibility," Salomão said.

Call center management wanted to scale services to not only align with the company’s growth, but to expand its services to clients who wanted to outsource their service desk operations with Accenture.

However, Accenture Brazil’s call center operations required major investments in on-premises infrastructure, preventing it from gaining the agility and cost effectiveness it needed to grow.

Since the regulatory environment in Brazil at the time prevented Accenture Brazil from fully migrating away from the country's local telecom infrastructure, Accenture Brazil worked with AWS to implement a hybrid solution, running Connect Customer integrated with the existing telephony infrastructure.

The new platform allowed Accenture Brazil to extend beyond internal requests, and act as a contact center-as-a-service for its international clients.

When AWS introduced Connect Customer in 2017, Accenture Brazil was confident that the platform could provide a simple, scalable, secure, and cost-effective foundation for its call center infrastructure.

Transparency Evidence & methodology 90/100 reference value · 90% confidence · 2 sources

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 value90/100

Problem clarity20/20
Measures whether the customer's operational problem is specific enough to compare.
Implementation depth15/25
Rewards named components, data flow, integrations, and architecture detail.
Outcome specificity20/20
Measures whether the reported benefit is concrete rather than a generic claim.
Quantified impact25/25
3 metrics describe measurable impact.
Deployment scale10/10
Rewards evidence of a live or scaled deployment and meaningful integration scope.

Evidence confidence90%

Source authority20/25
The main evidence is an official vendor-published customer story.
Claim traceability23/25
11 of 12 key fields link to a named source.
Direct evidence20/20
6 direct source quotes retained.
Date provenance8/10
The publication date comes from publisher-controlled metadata.
Source transparency9/10
2 source references document publisher, URL, authority, retrieval, and supported fields.
Implementation specificity10/10
Rewards 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.

AWS
Accenture Brazil customer story

First-party
https://aws.amazon.com/solutions/case-studies/accenture-brazil

Source type
Vendor-published customer story

Published
Jan 1, 2024
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
Accenture
Accenture Fact Sheet Fiscal 2026 – Fourth Quarter

First-party
https://newsroom.accenture.com/fact-sheet
The fact sheet reports approximately 814,000 people at fiscal 2026 year-end.

Source type
Official fact sheet
Supports
- Company size

Date evidence

Publisher catalog date Jan 1, 2024 · AWS · First-party
Open date source

Not separately sourced Industry, Region. Treat these normalized attributes as lower-confidence until a dedicated source is added.

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