Put AI to work.

Your team uses AI. The business still runs through manual handovers.

AI is often used to write emails, summarise meetings, and handle small tasks. The real work still begins with somebody finding files, opening several systems, moving data, and working out what has already happened.

AI rarely lacks intelligence. It lacks access to the work actually taking place.

what we hear

01

We use AI to write emails while people still move the same information between systems.

02

We have a CRM, inboxes, projects, and perhaps a finance system, but employees still have to hold it all together.

03

We can see that AI should help more, but it does not know our customers, workflows, or data.

Recognise two of the three and you probably have a workflow problem, not an AI-tool problem.

When AI can see the right context and stop at human decisions, it can begin to do the work.

gathering company contextwhat the business already knows

the symptom

The context exists.
AI cannot use it together.

Prices, quotes, call notes, delivery promises, and customer history already exist. They are simply spread across the tools your company uses.

CRMPipelineHubSpot · Pipedrive

ADSAd accountsGoogle Ads · Meta

WEBWebsiteShopify · WordPress

FINFinancee-conomic · Dinero

MAILInboxGmail · Outlook

DOCSFilesDrive · SharePoint

CALCalendarGoogle · Outlook

PHONECallsTeams · Aircall

SHEETSpreadsheetsExcel · Sheets

FLOWAutomationsn8n · Zapier · Make

PMDeliveryAsana · Jira

SUPSupportZendesk · Intercom

what we build

One system,
speaking to itself.

↓ keep scrolling — it gathers as you go

One request can start a real piece of work.

A simple request can set real work in motion because context, rules, and approvals are already in place.

This is already how we work.

We do not begin with a giant transformation programme. We solve the next real problem and keep the context connected when the company needs to move further.

ecommerce · Denmark

From Meta Ads to a connected ecommerce operation.

Companyshop24 first hired us for Meta Ads. The work expanded into Shopify, product and supplier data, website content, SEO, GHL, lead handling, Google and Meta, and freight workflows.

Once the systems, scripts, data, and rules connect, we can work across the operation from one technical environment. A large product import, change to the store, performance question, or freight workflow no longer begins by rebuilding the company context from scratch.

construction · Denmark

From personal accounts to one shared way of running the company.

Parlo Byg was working across personal email accounts, scattered files, and admin processes understood by only a few people. We built the Microsoft 365 setup, shared inboxes, and shared structure around Outlook, OneDrive, and SharePoint.

Ordrestyring then became part of the same working context. The owner can work across email, building cases, suppliers, materials, and admin information without searching every system manually first.

services · France

Real customer outcomes fed back into acquisition.

AJFR did not want another isolated automation. We connected Airtable, Make, Webflow, Calendly, Google Ads, tracking, and the company's CRM and revenue data.

Leads can be followed from their first enquiry to later commercial stages, and those outcomes can be returned to Google Ads. That gives the acquisition system something more useful to learn from than form submissions alone.

There is no single AI solution. There is work getting in the way.

Start with a workflow that is both felt and contained.

When context comes with the work, it can actually move forward.

The larger difference is that work does not start from zero every time.

“We want AI for quotes” is rarely one job.

It sounds like one thing. In practice, it usually involves several jobs, different data, and different decisions.

• 01Find the customer, project, and pricing information.
• 02Check it against company rules and previous work.
• 03Prepare the first draft.
• 04Route it to the right person for review.
• 05Update the systems that need to follow afterwards.

We break the workflow apart before deciding what AI may do and what a person still owns.

The work is not one prompt.

A useful workflow starts with a trigger, gathers context from the right systems, carries out several steps, and stops where a person should decide.

Quoting is the first of four examples. The three others are in the interactive walkthrough below.

AI only works once it has something real to work with.

Start with what costs the most. Build further once it works.

Bring the workflow that eats time, creates delays, or depends on one person.

first engagement

AI review

We assess whether one workflow is worth building.

Book an AI review →30 minutes with Kaan, who builds it

You leave with

• 01A clear picture of how the work happens today
• 02Where time, delays, or losses sit
• 03The systems and information required
• 04What AI can take on and what stays human
• 05An honest recommendation to build or leave it alone

Build the first workflow. Choose who runs it from there.

We can build and hand the solution over to your team, or remain responsible for operation and further development.