QUICK SOLUTIONS AI

AI agency · Innovation arm

AI systems that make it to production.

We are your company's AI innovation arm: an applied research team that follows every new release in the market, tests it with your data and puts into production what delivers performance and savings. Something ships every month, and the code stays with you.

Talk to the teamSee projects
7,000+
commits in 2026
900k+
lines of code
14k+
automated tests
8
systems on this page

Your innovation arm

An AI team working for your company, without you having to build one.

Building an in-house AI team takes months and rare people: someone to research, someone to test, someone to build and someone to run it. The agency plays that role alongside your team and your IT, with one backlog and one monthly meeting to decide the next step.

It works alongside your IT, not instead of it.

  1. Radar

    Watches the market for you

    Models, tools and prices change every week. You get what matters for your business, not the headline.

  2. Lab

    Proves it before you invest

    Every idea becomes a test on your use case and approval criteria written up front. What fails, fails cheap.

  3. Production

    Ships it and runs it

    What passes becomes a system integrated with the tools you already use, with every AI decision logged and its cost tracked.

  4. Knowledge

    Keeps the learning in-house

    Code, data, documentation and training stay with your team. Nothing depends on a single person.

Three ways to bring AI into a company

Hire an in-house team

To get started
Months of recruiting and hiring
How you pay
Fixed payroll of specialists
New market releases
Depends on who you hired
The knowledge
Leaves when they leave

Project-based consulting

To get started
Weeks of proposals and scoping
How you pay
A new budget for every idea
New market releases
Out of scope
The knowledge
Leaves with the vendor
How Quick works

AI agency as your innovation arm

To get started
First delivery in the first month
How you pay
Predictable monthly fee, auditable hours
New market releases
Part of the service, every week
The knowledge
Documented and handed to you
See how to hire us

Featured case · Healthcare · Medical practice

Estação Clínica

See patients face to face. The note comes out ready for you to review.

The practice's platform: scheduling and patient intake over WhatsApp, lab result reading, a consultation scribe and a clinical copilot. Every sentence the AI writes points to where it came from, and nothing reaches the patient without the doctor's sign-off.

Visit the product websiteSee the full case
Inside, in twelve screens. The real system, with a fictitious patient and lab results. A minute and a half, no sound.

Telehealth

Video consultations happen inside Estação.

Patients get the link on WhatsApp and join from their phone, with nothing to install and no password. You record with one click, and the note comes out ready, just like in person.

  • 01

    No app, no password

    The link arrives on WhatsApp and opens on the patient's phone.

  • 02

    Direct, private call

    Peer to peer between the two devices, or through the clinic's own server when the network requires it.

  • 03

    The transcript knows who spoke

    Your voice and the patient's are recorded separately, with no guessing by the AI.

  • 04

    Works with Meet too

    In Chrome or Edge, Estação records your microphone along with the meeting tab's audio.

Visit the product websiteestacaoclinica.com.br

Projects

What's already running

Large platforms, built and run by the same team. The numbers come straight from the repositories.

See all projects
Free-text job material list converted into catalog items, with one item not found and suggestions

Retail · Building materials

In production

AstroMatCon

A full ERP for building materials stores, with AI where it saves typing.

Sentinela9

Maestro

Decision: reads the whole case and decides where it goes next.

  • Porteiro

  • Escrivão

  • Clínico

  • Auditor

  • Perito

  • Elo

  • Vigia

  • Analista

Occupational health · Auditing

Being rolled out

Sentinela

Nine AI agents audit occupational health records before errors turn into liabilities.

Playground with four coordinated AI agents answering a question about campaigns

SMBs · Marketing, sales and customer service

In production, launching in October 2026

Jundo

An AI suite for the whole sales cycle: attract, convert and retain.

Requirements gathering

In production

Ideia Estruturada

The AI-led requirements gathering that opens every one of our projects.

The foundation

One foundation, many products. The next system starts out ready.

Estação Clínica and Sentinela were built on the same base. What was solved in one carries over to the next, so your project starts in the middle, not from scratch.

  1. Anonymization

    Personal data never reaches the AI

    Names, ID numbers and addresses become pseudonyms before any call. If something cannot be pseudonymized, the call does not go out. The answer is re-identified only on your screen.

    On screen

    Joana Exemplo, 54, ID 000.000.000-00, lives in Santos

    What goes to the AI

    [PATIENT_1], 54, ID [ID_1], lives in [CITY_1]

    Example with fictitious data.
    • A ledger of every call: what went in, what came out and what it cost
    • Data hosted in Brazil

  2. Agents

    Every agent has a role, rules and a version

    Agents work as a team, each with a clear job, and cite the source of what they say. None of them changes behavior without a version you approved.

    • Porteiro
    • Escrivão
    • Clínico
    • Auditor
    • Perito
    • Elo
    • Vigia
    • Analista
    • Maestro
    Sentinela's agent team
    • The AI proposes, a person decides
    • 9 agents in Sentinela, 10 tools in Estação

  3. Learning engines

    It improves with use, and the improvement is measured

    Every human review and every measured result becomes a benchmark. Rules, prompts and models are recalibrated and compared with the previous version before they go live.

    1. 1Human review
    2. 2Becomes a benchmark
    3. 3New version
    4. 4Compare and approve
    • No improvement ships without beating the benchmark
    • What we learn goes back into the queue

Why it speeds things up

01

The next product inherits everything

Security, logging, WhatsApp integration and versioned agents come ready.

02

You don't pay twice

The base is the same across systems. The budget goes to what is new.

03

From the middle, not from scratch

Each cycle starts with the business problem, not with infrastructure.

No lock-in

The source code is yours. You're not tied to a vendor.

  • Code, infrastructure and documentation

    Yours from day one. If you leave, you take everything.

  • Swappable AI provider

    The model is chosen per task and can be swapped, with quality measured against a benchmark before the switch.

  • Another team can take over

    The documentation exists so the operation doesn't depend on us.

Applied research

We follow what the market ships and put it to work when it pays off.

Every week we read new model releases, papers and tools. What looks promising, we test in Portuguese, on the client's use case, with pass criteria written beforehand. Only what brings measured performance or savings goes into production.

From release to production

  1. Releases read every week
  2. Tested in Portuguese, on the actual use case
  3. Approved against criteria written up front
  4. In production, being measured

Recent example

Jev, by TypeSafe AI

A new model that does not write text: it answers closed questions (“did the person ask for an agent?”) with a calibrated probability. We studied it, tested it on 123 cases in Portuguese and connected it to two systems: in Jundo it runs in shadow mode, observing without deciding; in Estação Clínica it already flags answers for the team to review. If the provider goes down, the flow carries on as before.

Accuracy on requests for a human agent

Previous model
67,5%
Jev
100%

Latency per decision

Previous model
1×
Jev
÷8

Cost per decision

Previous model
1×
Jev
÷70

Test on 123 hand-written (synthetic) cases in Portuguese, September 2026. Latency measured from the development machine.

Read the full note on Radar

What we already do to spend less

Rules before AI

In AstroMatCon, 97.5% of invoice items are matched without calling AI.

The right model for each task

In Estação Clínica, as spending nears the cap, the system switches to a cheaper model on its own.

Cheapest path first

In AceleraMatCon, spreadsheets are read without AI, PDFs with light AI, and only photos use vision.

Switch providers without rewriting

In our systems the AI provider can be swapped per task, and quality is measured against an answer key before any switch.

The problem

A 12-month project gets approved on assumptions that have already changed by month 4.

Every idea becomes a new proposal, with the scope locked before anyone has learned anything. By the time the system is ready, the problem has moved, and the know-how leaves with the vendor.

One project at a time

  • A new proposal for every idea
  • Scope locked before learning
  • Delivery at the end, when everything has changed
  • Knowledge lost between one project and the next

An AI agency

  • One backlog, prioritised by you
  • A team that already knows your business
  • Something live every month, measured and shown
  • Code, data and documentation stay with you

What the agency does

We look for where AI pays for itself, and build that.

We don't resell tools. We look at your operation, find where AI saves time or money, and put it into production.

What the agency does
01

WhatsApp and support agents

They answer, book, take orders and transcribe voice notes. Every conversation is logged, and a person steps in when needed.

See the area
02

Process automation

Routines that run on spreadsheets, email and copy-paste today, handled by agents with steps you approve.

See the area
03

Document reading

PDFs, lab results, invoices and contracts become structured data, each value next to the passage it came from.

See the area
04

Predictive models

Demand, restocking and pricing forecasts, calibrated on your company's own history.

See the area
05

Custom systems

When off-the-shelf software doesn't fit, a system of your own, with AI built in.

See the area
06

Data and decisions

Dashboards and alerts that flag risk early, measured the way you define.

See the area

How we work

One cycle a month, with you at the table.

See the full method
1 cycleper month01020304

What we learn goes back into the queue.

  1. 1

    Prioritise

    You pick the next pain point from the backlog. We tell you what it costs and how we'll measure it.

  2. 2

    Build

    Short deliveries, live early, on the same secure foundation.

  3. 3

    Measure

    Against the yardstick agreed upfront: time, cost, errors or conversion.

  4. 4

    Show

    At the monthly meeting: what changed, what it cost and what comes next.

Which process in your company would you like to stop doing by hand?

Tell us in one message. We'll reply with a scheduled conversation, not a generic deck.

Book a callMessage us on WhatsApp