Lab

See how the automation actually works.

Interactive demos with simulated data. You can watch a process get read, decided and carried through step by step, not just the end result.

24

live demos

Simulated data, real logic

Engine room

The engine room, hood open.

Four systems that don't just show the result. They show the automation reasoning, fetching data and, where it matters, pausing to wait for a person.

orchestrator.run()
AI
Incoming email
Classifier
Back-office data
Human approval
Send + CRM

// scegli uno scenario per avviare il flusso

rag-inspector.query()
AI

Pick a real question, the kind that blocks work:

Retrieved documents

// pick a question to see where the answer comes from

document-parser.scan()
AI
BIANCHI HARDWARE LTD 41 Roma St, 20900 Monza VAT IT02845670961 INVOICE no. 2026/0412, 07/12/2026 Stainless screws 4×40 (box 500) € 180.00 Nitrile gloves M (×200) € 260.00 Drill B-750 (×4) € 800.00 Subtotal € 1,240.00 VAT 22% € 272.80 TOTAL € 1,512.80

Extracted data

// press "Scan document" to see the extracted data

whatsapp-autopilot.console()
live

Hi! I’m Moretti Garage’s assistant. Ask me about prices, appointments, urgent requests.

Agent console

// tap a quick reply to see what the assistant is thinking

Incoming email

The inbox that empties itself.

The agent reads every incoming email, classifies it and drafts a reply ready for your approval.

email-agent.inbox()
AI

Inbox

Draft reply

// pick an email to see the generated draft

Before

Every urgent email waits for someone to find the time to read and answer it.

After

The agent reads, classifies and drafts the reply: you approve with one click.

-70%

response time

24/7

inbox coverage

Instant quotes

The quote is ready before your coffee.

It always uses the current price list. You pick what's needed and the agent builds the document in seconds.

quote-agent.generate()
AI

Pick what needs a quote:

Quote generated

// press "Generate quote" to see the result

Before

Quotes get written at the end of the day, between customers, often off the wrong price list.

After

The agent pulls the current price list and builds the quote while the customer is still on the phone.

< 2 min

from request to quote

0

pricing errors

Document archive

The answer you were hunting for an hour.

Ask a real question, the kind buried in a contract or an old email. The agent finds it and names the source.

knowledge-base.ask()
AI

Ask something that usually means digging through a thousand files:

Assistant answer

// pick a question to see the answer

Before

The answer lives in a contract, a manual, or a three-month-old email. Nobody can find it anymore.

After

Ask in plain language, the agent searches your own documents and always names its source.

-90%

time to find an answer

1 source

always cited

Contacts & leads

The right lead, before anyone else.

Every new contact gets scored instantly, with the factors, the score and the recommended next move.

crm-agent.score()
AI

Incoming leads

Lead score

// pick a lead to see the score

Before

Every new lead lands at the bottom of the pile, treated the same as everything else.

After

The agent scores it right away and flags who to call first, and why.

+35%

leads contacted within an hour

3 factors

in the score

Customer care

The angry customer, handled in a minute.

The agent detects the tone, sets the priority and drafts the reply. You review it and send it.

customer-care.triage()
AI

Ticket queue

Proposed reply

// pick a ticket to see the proposed reply

Before

An angry customer writes at 7pm, the reply arrives the next day.

After

The agent reads the tone, drafts a reply, and queues it for your approval.

-60%

first-response time

100%

tickets triaged

Data entry

The data enters itself, you stay in control.

Any format, such as WhatsApp messages, handwritten notes or email, becomes a record ready in the back office.

data-entry.extract()
AI

Pick the source to process:

Hi! I need 3 boxes of nitrile gloves size M and 2 B-750 drills, I’ll pick them up Friday morning if that works, thanks

Record created

// press "Extract and load" to see the structured record

Before

Orders via WhatsApp, handwritten notes, email: someone retypes each one into the back office.

After

The agent reads any format and creates the record ready in the back office.

0

manual retyping

< 30s

from message to back office

Readiness assessment

You don't know yet, now you will.

5 questions to see how ready your business really is, and where to start.

ai-audit.run()
AI

Before

You know you could automate something, but not what or where to start.

After

5 focused questions tell you where you stand and what the first step is.

5

questions

2 min

to finish the test

More demos

The rest of the toolbox, in compact form.

Thirteen smaller automations that follow the same principle. They read the data, make a decision and give you time back in your day.

Multilingual WhatsApp

The customer writes in their language, the agent replies in yours.

// pick a message to see the generated reply

Voice mailbox

The voicemail becomes text, with a draft reply already prepared.

// pick a message to see the generated reply

Dormant customer recall

Finds customers who’ve gone quiet for months and drafts the message to bring them back.

// pick a message to see the generated reply

Payment guardian

Flags at-risk invoices before they become a real problem.

// pick the flagged item to see why

Deadline radar

Contracts, warranties, renewals: no deadline catches you off guard again.

// pick the flagged item to see why

Ghost quote hunter

Finds quotes that were sent and never followed up, before the customer picks another supplier.

// pick the flagged item to see why

Cashflow radar

Cross-checks expected income and outgoing payments, flags a possible cash gap early.

// pick the flagged item to see why

Reviews

A review request goes out automatically right after the service is delivered.

+40%

reviews collected

Payment reminders

Automatic reminders before and after the due date, tone adjusted to how late it is.

-50%

average days to get paid

Bank reconciliation

Every bank transaction gets matched to its invoice, nothing retyped.

0

manual matches

Smart calendar

Appointment confirmations and reminders go out on their own, cutting last-minute no-shows.

-30%

missed appointments

Smart shifts

Suggests the week’s shifts based on availability and expected workload.

< 10 min

to plan the week

Funnel thermometer

Shows how many contacts move from first touch to paying customer.

34%

leads that become customers

How much you can save

The math in time and money.

Drag the sliders to your numbers. The formula is right below. No magic.

Estimated yearly saving

€20,800

832 · Hours back per year

hours × people × 52 weeks × hourly cost

This is a rough estimate and not a promise. It gives an order of magnitude, not a quote.

How it starts

From week one to month three.

We go one process at a time rather than changing everything at once, and we measure at every step.

  1. 01

    Week 1-2

    One process, not everything

    We pick the process that hurts most and automate it first: visible result right away, minimal risk.

  2. 02

    Month 1

    Run-in and measure

    The first automation runs on your real data. We adjust where needed and measure the time actually saved.

  3. 03

    Month 3

    It grows

    With the trust built, we add the other processes one at a time, connecting the tools you already use.

Before and after

What changes, concretely.

The same tasks, how they were and how they become.

TaskBefore, by handAfter, automatic
QuotesRetyped by hand, hours of waitingDraft ready in minutes, data already in
Incoming emailInbox overflowing, late repliesSorted, with a draft already prepared
Data entryCopy-paste from PDFs and invoicesExtracted automatically, you confirm
Deadlines and renewalsFound at the last minuteFlagged in advance
Getting paidForgotten remindersAutomatic reminders, faster payment
Dormant customersForgotten for monthsSpotted and re-contacted

How we see it

Not magic, method.

Three principles that hold for every automation we build.

Simulated data, real logic

The numbers in these demos are made up to show you the mechanism. The logic underneath, though, is exactly what we actually build.

The human decides where it counts

The automation prepares, proposes, flags. The decisions that matter stay yours: where needed, the system stops and waits for you.

It starts with one process

You don’t need to overhaul the company. You automate the piece that hurts most, measure it, and only then expand.

Want a flow like this in your business?

These demos run on simulated data. In a readiness assessment we look at your real processes together and find which ones are worth automating first.

Request an assessment