SUCCESS STORY
The company faced a major challenge: a growing volume of support requests, many of them repetitive, combined with a support experience that no longer reflected the simplicity of the product. You can see the solution in this case study.
Metric | Result |
|---|---|
Tickets resolved per month | +3 thousand with AI |
Average resolution time | 5 hours (before: 22 hours) |
Ticket retention | +70% resolved by AI |
About Conta Simples
Conta Simples is a fintech created to simplify companies' financial management, promoting greater control over expenses, organization, and financial management.
In customer service, many interactions involve urgent situations, such as difficulties making a payment, transfers, or other financial operations.
In this sense, the CX team needed to handle a large volume of requests, many of which were repetitive. Questions alone accounted for about 35% of the interactions received by the operation.
The customer service experience did not reflect the product
Before the transformation of its operations, Conta Simples used a traditional chatbot model based on menus and support flows. In this format, the customer had to navigate through several options before being able to explain their issue.
Challenge | Description |
|---|---|
Rigid support experience | Support was based on a traditional chatbot with menus and multiple options. To explain an issue, the customer had to go through different steps until they could describe what they needed. |
High volume of repetitive questions | A large share of the interactions received by support were related to operational questions or guidance on using the platform (about 35%). |
Operation scale limited by the traditional model | As the company grew, the volume of tickets kept increasing. Even with adjustments to the chatbot and attempts to reorganize the operation, the model still had limitations in scaling with quality. |
Support required excessive effort from the team | Even simple questions kept reaching the human team, consuming the team's energy and limiting the operation's ability to act more strategically. |
To deal with the increase in volume, Conta Simples even tested alternatives such as reorganizing the support flow and even using outsourced support to absorb part of the demand.
Even so, the problem persisted. The model continued to require a great deal of human effort to resolve simple questions, while the company's product promised precisely simplicity and efficiency for its customers.
“The customer had to navigate among options such as question, request, or issue until they could explain what they wanted.
This made support slower and less intuitive.”
Amanda Rodrigues
Support Coordinator at Conta Simples
A new approach to customer service
Facing an operation strained by recurring questions, queues, and a support model that no longer matched the product’s simplicity promise, Conta Simples decided to reorganize support with AI as part of the operation.
Main changes:
A significant portion of recurring questions began to be resolved by ClaudIA acting on the front line of support.
The human team stopped concentrating energy on repetitive demands and began to focus more on context, quality, and customer experience.
AI began to operate integrated into the operation, with the ability to consult internal systems and support case resolution beyond basic answers.
The operation began to have a continuous audit and improvement routine, tracking retention, handoff, and opportunities to adjust AI’s performance.
Support gained more scale without increasing team overload, allowing the company to grow with more predictability in operations.
“AI does not replace people, it frees the team so they can provide more strategic support.”
Amanda Rodrigues
Support Coordinator at Conta Simples
From the knowledge base to ClaudIA's continuous evolution
The implementation of AI at Conta Simples began by organizing the knowledge that already existed within the operation.
Since the team already had FAQs and well-defined processes, the focus shifted to teaching ClaudIA how to act based on this content, translating each journey into a clear logic of problem, solution, and tone of voice.
Stage | Title | Description |
|---|---|---|
01 | Structured knowledge base | Before activating ClaudIA, Conta Simples already had FAQs and well-defined processes. Implementation began by turning this knowledge into operational logic for the AI. |
02 | Tone of voice and escalation criteria | The team defined how the AI should respond, what it should keep, and which situations should be routed to human support. |
03 | Integration with internal systems | After the first few months handling simpler questions, ClaudIA began to connect to Conta Simples' systems to consult information, recognize customers, and resolve cases with more context and security. |
04 | Auditing and continuous improvement | The operation began to rely on a dedicated person to monitor what the AI retains, what escalates, and why. Every mistake became a learning opportunity, and every adjustment began to improve the experience and retention. |
As the operation matured, ClaudIA stopped acting only as a resolver of basic questions and began to respond with more context, consult systems, and even anticipate messages in unstable scenarios. This turned the implementation into a continuous process of evolution, not a one-off project.
“We had FAQs and well-defined processes within support. We just needed to teach ClaudIA how to act given this content.”
Amanda Rodrigues
Support Coordinator at Conta Simples
Transformation into numbers
With ClaudIA integrated into operations, Conta Simples began to absorb a large share of the simplest and most repetitive interactions, reducing the team's operational effort and speeding up case resolution. The impact was seen both in operational efficiency and in the customer experience.
Metric | Result | Impact |
|---|---|---|
Interactions handled by AI | 70% | Most of the volume began to be resolved without direct human intervention. |
Tickets resolved per month | ~3,000 | Significant reduction in the team's operational workload. |
Average resolution time | 22h → 5h | AI began to absorb a large share of interactions without escalation (+23,000 cases). |
Instead of concentrating energy on recurring questions, the team began to focus on critical cases, quality, and improving the customer experience. In practice, this meant a lighter operation, with less overload for the team and more room for strategic work.
AI does not replace people; it frees the team to provide more strategic support.”
Amanda Rodrigues
Support Coordinator at Conta Simples
What Conta Simples learned in the process
Theme | Description |
|---|---|
AI does not replace people. | By taking the burden of repetitive questions off people, the operation gains space to focus on quality, context, analysis, and customer experience. |
Continuous auditing is central to AI success | Conta Simples understood that tracking escalations, reviewing responses, and quickly correcting what goes off track is what ensures quality and the operation’s long-term evolution. |
Scaling support with quality requires balance between AI and humans | The goal was never to retain everything at any cost, but to resolve efficiently and ensure that sensitive or urgent cases were properly routed to human support. |
There is no good experience with an overloaded team | One of the main gains noticed was the team’s operational lightness, which led to more focus and less strain. |
“Don’t try to do everything alone. Have AI as your ally. Step away from that operational chair, let it do that, and sit in a strategic position where you can truly add value to your company.”
Amanda Rodrigues
Support Coordinator at Conta Simples
Cloud Humans answers
Did AI replace Conta Simples’ support team?
No. The company kept the same number of people and began using AI to absorb recurring questions, freeing the team to focus more on quality, context, and strategy.
How was ClaudIA trained to support Conta Simples’ customers?
The implementation started from the knowledge base the company had already structured, such as FAQs and internal processes. From there, the team taught the AI the logic of the journeys, the retention and escalation criteria, and the brand’s tone of voice.
Does AI handle everything by itself?
No. Some cases are intentionally routed to human support, especially when they require deeper investigation, faster action, or greater sensitivity in resolution.
What ensured the quality of the operation after implementation?
Conta Simples set up a continuous audit routine for conversations, tracking what the AI retained, what it escalated, and why. This monitoring became central to quickly correcting errors and improving ClaudIA’s performance over time.
Does AI work well in a financial operation?
Yes, especially when integrated with the company’s systems. With integrations and queries to internal data, ClaudIA began operating with more context and security, which is very important in a fintech operation.
