What we do

Your company, with superpowers.

We help you find where AI actually pays off in your business, and then we build it. New processes, working code, and agents that keep it running. Not a pilot deck. Something your team uses on Monday morning.

Book an introduction See what that means

4–8 wks To first value

Fixed fee Monthly

Your code Your custom code

Where the work happens. Two people, one problem, one afternoon.

Press release · 17 August 2026

Emberloom AI is open for business.

Stockholm, 17 August 2026. Emberloom AI has started operating. The company builds tailored AI solutions for e-commerce: new processes, code that fits how a business actually works, and agents that keep it running. Emberloom AB was registered on 13 August 2026 and is the legal entity behind the brand.

The three founders came at the same problem from three directions. Emma Ekström takes the role of CEO, coming from projects and change with software and engineering underneath, and years in sales and business development. Adán Hultgren takes a seat on the board, bringing large systems, robust solutions and fifteen years of building what holds up in production. Stefan Sånnell has been a consultant and a CEO, worked inside software companies and in line roles, and held CTO, CDO and COO positions across e-commerce and ERP programmes. At Emberloom he commissions the code and develops the concept.

They spent the past period experimenting on real client work rather than in a lab, and kept arriving at the same conclusion.

The conclusion is that most e-commerce companies do not need another system. They need the operational layer that should have existed between the ones they already pay for. Emberloom AI builds that layer, puts agents inside it rather than beside it, and leaves the code with the customer. The first measurable use-case runs in production in four to eight weeks, on a fixed monthly fee.

Behind the delivery sits a platform in three parts. SafeZone keeps operations and data inside the EU. GuardRails reviews every line of AI-generated code before it ships. FastTrack is the method and the reference model, drawn from more than a hundred e-commerce implementations and queried through a knowledge agent.

The company runs with significantly more AI agents than people, by design. It intends to keep it that way, scaling through agents rather than headcount, which is why a team this size can take on the work it does.

Emberloom AI is opening up to one or two more people. The profile is someone who moves easily between business and technology, speaks e-commerce fluently, and wants to help build the toolbox rather than only use it.

About Emberloom AI. Emberloom AI builds custom AI solutions for e-commerce companies that want to own what they run. The name comes from the loom, the first machine in history driven by a program instead of by a hand, and from the ember that keeps glowing after the room has emptied. The company trades as Emberloom AI. Emberloom AB is the legal entity that signs.

Contact. hello@emberloom.ai

The superpowers

Processes, code, and agents.

New processes

Most AI work fails before a line of code is written, because nobody looked at how the work actually flows. We start by finding the place where your people are the integration engine between systems. That is where AI is worth building, and the rest is noise.

How we find it

Code that fits you

AI made writing software cheap enough that tailoring it is finally the sensible option. So we build the thing that matches how you work, instead of bending your operations to fit a product built for the market average. You own the code.

What we build

Agents that keep it running

Not chatbots off to the side. Agents inside the operation, reading the same data as the team, handling the routine cases, flagging the ones that need a human. They work at night and they do not forget what happened last Tuesday.

See it in production

The cost of doing nothing grows every quarter.

What it costs today

You are paying full price for a fraction of the value.

Count your licences. Across the implementations we've run, most companies use somewhere near a tenth of what they pay for, and the tenth they actually need is the part the vendor never built. See it in the cases.
Then count the integrations. Each one was expensive to build, is expensive to keep alive, and moves a handful of fields between two systems that were never meant to meet.
Every new market adds another system, another login, another manual sync. It compounds, and it never compounds in your favour.
The usual answers are a twelve-month enterprise programme or living with it. Neither one is a plan.

When building costs a fraction of what it did, the maths changes. A system you use a tenth of becomes a candidate for replacement, not a fact of life. We weave data, processes and systems into a pattern you can run again every day, without anyone having to remember how it went the first time.

Where the work happens

A dashboard shows you the number. A command centre runs the work.

Your systems each understand their own objects. The PIM knows products, the ERP knows orders, the WMS knows stock. Real work crosses all of them, which is why it ends up in Excel and Slack. The layer we build sits on top and gives the work somewhere to live.

Dashboard

One place where the numbers agree. It reads from the source systems, so management and the team look at the same reality instead of a report that was true on Tuesday.

See it

Command centre

Here is the anomaly, here is the cause, here is the suggested action, here is who approves it, and here is the log of what was done. The work is not reported on somewhere else. It happens here.

Run it

Agent operations

Agents work inside the same command centre as the team. They take the routine cases, follow the rules you set, and escalate everything that falls outside them.

Hand it over

Fewer systems to pay for

Once the operational layer holds the work, the systems underneath get easier to question. Some stay. Some get replaced by something that costs less and fits better.

Then subtract

Room to think. What is left when the routine work leaves.

From individual to team

Everyone got faster. The company did not.

The first wave of AI landed with individuals. People write quicker, summarise quicker, draft quicker. The gain is real, and it stops at the edge of one person's desk. Nothing about the way the team works has changed, so nothing shows up where you measure.

The step that matters is moving that leverage into shared work. A command centre is where individual speed turns into team throughput, because the process, the data and the decisions all sit in one place instead of in twelve inboxes.

And the second effect is the one people underestimate. When the routine work goes somewhere else, what is left is the work that needs a human: the judgement, the negotiation, the idea nobody asked for. Efficiency and creativity are not a trade-off here. Getting one is how you afford the other.

The platform

Three parts. One coherent way of building with AI.

SafeZone

Operations inside the EU. Your data stays in Europe, your models stay yours.

GuardRails

A quality framework that reviews every line of AI-generated code before it ships.

FastTrack

The method, the playbooks, the map of e-commerce, queried through a knowledge agent.

Three levels

Prove, replace, automate.

01 · Entry

One measurable use-case in production

We pick the highest-leverage problem on the table and ship it.

4–8 weeks

02 · Standard

Replace the SaaS you already pay for

CRM, PIM, BI. Software tailored to how you actually work, not to the market average.

8–16 weeks

03 · Enterprise

From replacing systems to replacing work

Agents, workflows, and a roadmap built with your operations team.

Ongoing

How it starts

Proof first, commitment later.

Introduction

We listen, you sketch the problem on the table, we say honestly whether we are a fit.

30 min

Walkthrough

We sit with your operations team and map the systems, the people, and where the leverage hides.

1–2 weeks

Entry pilot

One measurable use-case, in production, on a fixed monthly fee. You decide what success looks like up front.

4–8 weeks

What comes next

Standard or Enterprise, only if the pilot earned it. You keep the code either way.

Ongoing

The weave. Someone still has to set the pattern.

The name

Loom is the weaving frame. Ember is the glow.

In 1804 Joseph Marie Jacquard fitted punched cards to his loom in Lyon. For the first time a machine was driven by a program instead of by a hand. The cards went on to Hollerith, to IBM, to the computer.

A company is threads that have to hold together: data, processes, systems, people. None of them means anything on its own. What we deliver is not one more thread, it is the weave.

Ember is the glow that stays and keeps burning after the fire has died down and the room is empty. It needs no tending, it holds the heat, and it is what you carry to the next fire.

We are also hiring

Room for one or two more.

If you move easily between business and technology, speak e-commerce fluently, and want to help build the toolbox rather than just use it, we would like to hear from you.

Read what we are looking for

Your team deserves better tools.

If you are running on five systems or more and spending hours on work that software should handle, get in touch.

Thirty minutes. No prep needed. We will tell you honestly whether we can help.

Book an introduction hello@emberloom.ai