AI-Powered Customer Service
We design customer service where AI resolves the frequent requests (order status, appointments, invoices, account changes) on WhatsApp, web chat or email, using your systems' real data. When the case needs a person, the conversation passes to your team with the context already gathered, so the customer does not have to repeat anything.
Who It's For
Companies with a high volume of repetitive customer requests: retail and e-commerce, financial services, insurance, health, education, utilities and B2B companies with demanding after-sales. Especially useful when the volume grows faster than the team, when customers write outside business hours or when the current bot only answers with menus and ends up frustrating people. Ideal for customer experience, service and operations directors.
Deliverables
What You Gain
Immediate answers at any time
Frequent requests are resolved in the moment, including nights and weekends, on the channel your customers already use. Waiting in a queue for a simple question stops being the norm.
Your team focuses on the cases that need judgment
When repetitive requests are resolved automatically, agents have time for complaints, exceptions and sales opportunities, where a person makes the difference.
Conversations, not rigid menus
Customers write as they speak, with typos and several questions at once. The assistant understands the intent, asks for what is missing and responds in a clear tone aligned with your brand.
Answers with real data, not generic ones
The assistant checks the order, the invoice or the appointment in your systems and responds with the customer's concrete information, after verifying their identity when required.
Visibility into why customers contact you
Every conversation is classified by reason and outcome. You see which problems generate the most contacts and can fix the root cause in the product or the process.
Clear rules for what the AI can and cannot do
We define which topics it handles, which actions it can execute and when it must transfer to a person. Sensitive data is protected and every conversation is recorded for review.
Best Practices
Start with the top contact reasons
Analyze a sample of real conversations and group them by reason. A few reasons usually concentrate a large part of the volume: automate those first, with simple and verifiable answers, and expand from there.
Design the exit to a person
The customer must always be able to reach a person, and the transfer must include the summary of the conversation and the data already collected. A good handoff matters as much as a good automated answer.
Measure resolution, not deflection
A bot that "contains" conversations but does not solve them only moves the problem. Measure whether the customer's request was actually resolved, whether they came back for the same reason and how satisfied they were.
Write it the way your best agent would
Use the phrases, policies and judgment of your most experienced agents as the base for the assistant's answers. Review real conversations every week with the service team and adjust.
Patterns & Practical Cases
Customer service that works with AI combines an assistant that understands natural language, integrations to consult and update data in your systems, and an operation model where people supervise the quality and take the cases that need them. The channel matters: in Latin America, much of the conversation with customers happens on WhatsApp.
Self-service for frequent requests
Typical cases: checking the status of an order or a shipment, scheduling or rescheduling appointments, sending a copy of an invoice, updating contact details, answering questions about policies, coverage or prices with the current documentation, and opening a ticket with the right category when the request cannot be resolved in the moment.
Support for the human team
AI also helps the agents: it summarizes the conversation before the transfer, suggests the answer according to the policies, classifies the reason for contact and drafts the closing notes. The agent reviews and decides, and spends less time on administrative work.
Key patterns
Technology Ecosystem
AWS cloud contact center with chat, voice and messaging channels, generative AI capabilities for self-service and agent assistance, and pay-per-use pricing.
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Microsoft platform to build conversational agents connected to Dynamics 365, Teams and the Power Platform. A natural option for companies that already work with Microsoft.
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Google Cloud's conversational agents (formerly Dialogflow), with Gemini models, multilingual support and integration with contact center platforms.
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Open-source automation platform to connect the assistant with WhatsApp, CRM, ticketing and billing systems, with flows your team can maintain.
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For the custom integrations, conversation analysis and quality evaluation of the assistant: classifying contact reasons, measuring resolution and detecting answers that need review.
Learn more →Do you care about the experience on the other side of the chat?
We are looking for people who combine conversational design, integrations and AI, and who measure their work by the problems they solve for customers.
What to Avoid
Hiding the way to a person
Forcing the customer to go through endless loops before reaching an agent destroys the experience and the trust in the brand. The option to talk to a person must be clear and quick.
Letting the AI make up policies
An assistant without limits can promise refunds, discounts or conditions that do not exist, and the company may have to honor them. Answers about policies must come from the official documentation, and commitments must go through defined rules.
Measuring only how many conversations the bot "contained"
A high containment rate can hide customers who gave up without a solution. Combine it with real resolution, repeated contacts and satisfaction to know whether the service improved.
Launching on all channels at once
Start with one channel and a few contact reasons, learn from real conversations and expand. Launching everything at the same time multiplies errors and makes it hard to know what to fix.
What do your customers ask you the most?
THAT
RESOLVES
AND KNOWS WHEN
TO HAND OVER