Customer service agents
On WhatsApp, your website or email. They reply in your brand’s voice, check your systems and know when to bring in a person.
Artificial intelligence
AI that works
inside your operation.
Agents and automations that answer customers, read documents, look things up in your systems and log everything. With clear rules, protected data and people in control.
Where AI helps
It’s not about having AI.
It’s about lightening the load.
We start where work is repetitive, depends on reading and takes hours from skilled people. That is usually where AI makes a real difference.
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Customer service
The same questions, all day long.
An agent handles the repetitive questions, checks orders, schedules and records in your systems, and hands over to a person whatever needs attention.
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Documents and email
An inbox nobody can keep up with.
AI reads, sorts and extracts data from emails, invoices, contracts and forms, and puts each piece of information where it belongs.
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Knowledge base
The answer exists, but nobody can find it.
An assistant answers from your manuals, policies and history, and shows where each piece of information came from.
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Reporting
Hours spent building the same report.
Data gathered from several sources and summarised in the format management needs, as often as makes sense.
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System integration
People copying data from one screen to another.
Automations connect ERP, CRM, spreadsheets and tools, with AI handling the steps that used to need a human to read them.
- 08:15 new email · accounts@
- “Please find attached invoice 10482 for PO 3391.”
- → reading attachment: invoice (PDF)
- Alfa Packaging · 12 items · $4,870.00
- → checking against PO 3391 in the ERP
- items and amounts match
- → recording in accounts payable
- ✓ bill created and sent for approval
- 08:16 new email · accounts@
- “The amount on this bill isn’t what we agreed.”
- → outside the agent’s rules
- ✓ forwarded to the team with a case summary
Demo
An agent in the
accounts payable inbox.
In this example, the agent reads invoices that arrive by email, checks them against the purchase order in the ERP and records whatever is within the rules. Anything outside them goes to a person, with a summary ready.
- Reads attachments and extracts dataPDFs, images and email body, with no manual typing.
- Checks before actingMatches amounts and items with what is already in the system.
- Knows when to stopExceptions go to your team, who make the call.
Fictional scenario and data, created to illustrate how an agent works.
What we deliver
Four ways to put
AI to work.
Each project combines what your operation needs. Sometimes that is an agent; sometimes a simple automation does the job better.
Process automation
Flows that read, check, sort and record. Repetitive work leaves your team’s desk and happens on its own, fully logged.
Internal assistants
An assistant that knows your company’s knowledge base and helps the team find answers, draft documents and follow procedures.
AI in the systems you already use
AI features inside your ERP, CRM or company platform, such as document reading, summaries and natural-language search.
How we do it
Small, real and measured.
Then bigger.
We prefer to prove value on one well-chosen process before scaling up. That way, the investment follows the results.
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Step 1
Assessment
We map the operation with the people who do the work and choose where AI offers the most return with the least risk. Sometimes the answer is an automation without AI.
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Step 2
Prototype with real data
We test with examples from your operation, in a controlled environment, to see what works before investing in the rest.
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Step 3
Integration
We connect to your systems, define rules, permissions and human review points, and roll out to production gradually.
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Step 4
Ongoing care
We measure, fine-tune rules and instructions and keep up with how models evolve. The solution keeps being looked after.
Responsibility
Serious AI
doesn’t promise magic.
Good technology is technology you understand, control and can switch off. That is how we build.
- Your data, handled with care.
- We agree with you which data AI can access, where it is stored and for how long, in line with data protection law (LGPD). We favour setups where your data is not used to train third-party models.
- Clear limits.
- Every agent has a defined scope: what it can do on its own, what needs approval and what it never does.
- People in control.
- Sensitive decisions go through someone on your team. Every action is logged and can be reviewed.
- Honesty about what AI does.
- It makes mistakes, and we say so from day one. That is why we design checks, measure results and point out where it is not the right tool.
FAQ
What people
usually ask us.
Didn’t find your question? Tell us about your case and we will answer.
Let’s talkDo I need to replace my systems?
Usually not. AI connects to what you already use: ERP, CRM, WhatsApp, email, spreadsheets and in-house systems.
When a system offers no way to integrate, we look at the alternatives during the assessment and explain the pros and cons of each.
Is my data safe?
Security is part of the project from the start. We define which data AI can access, with what permissions, where it is stored and who can see the logs, in line with data protection law (LGPD).
We choose providers and settings suited to the kind of information involved and document those decisions with you.
How long does it take?
It depends on the process, the integrations involved and the current state of your data. That is why we do not give a timeline before the assessment.
Afterwards, we present the scope and a realistic schedule. We prefer to start with one well-chosen flow and expand from what works.
Does AI make mistakes? How do you handle them?
It does. That is why we never treat AI as infallible. Every solution has rules on what can be done without review, automatic checks (such as matching amounts against the system) and hand-off to a person when something is out of the ordinary.
Everything is logged. We follow up on the cases where AI got it wrong or hesitated and improve the solution based on them.
Does my data need to be organised first?
It does not need to be perfect. During the assessment we look at what exists and what is enough to get started. Often the project itself helps organise the information.
What happens when AI models change?
They change fast. We build solutions so the model can be updated or replaced without starting over, and we keep track of that as part of ongoing care.
Next step
Which trajectory does your
business need to change?
Tell us the challenge. We’ll come back with the right questions and a clear technical path, with no strings attached.