We find the repetitive processes that are prone to human error, and we automate them. We connect your existing software using n8n and webhook architectures, and we build large language model (LLM) integrations tailored to your CRM and databases.
This field has a lot of sales talk and not much actual delivery. Our approach: we don’t start by bolting AI onto something. First we measure how much time each task takes, then we decide whether that task is worth automating at all. Automating a task that takes two hours a month is usually a net loss.
Where we start
A good candidate for automation has three traits:
- It repeats. It’s done dozens of times a week, with the same steps every time.
- The rules are clear. If the answer is “it depends” too often, the process needs to be clarified first.
- Mistakes are costly. A piece of data entered wrong causes problems somewhere else later on.
In the discovery call we map out where your team’s day actually goes. Contrary to what most people expect, the biggest gain usually comes not from AI but from getting two systems to talk to each other.
What we build
Cross-system automation
Data flowing between your forms, email, CRM, accounting, shipping and marketplace systems. No more re-entering a record by hand from one system into another. We build it with n8n, webhooks and API integrations.
LLM integrations
Language model applications connected to your own data: classifying and prioritizing incoming requests, summarizing documents, drafting replies, and question answering over your own documents.
Human-approved workflows
For critical work, we don’t let automation run unsupervised. The system prepares the work, a person approves it with one click over Telegram or email, and only then is it carried out. That’s how we manage the risk of AI making the wrong decision.
Reporting and notifications
Periodic reports prepared automatically and sent to the right person; alerts that fire when a threshold is crossed.
Tools we use
n8n and Zapier for workflows, webhook and API architectures for connecting systems, and different language model providers depending on the need. Your data privacy requirements drive the choice of tools — if data must not leave your environment, we set things up to run on your own servers.
Process
- Process inventory. Which task, how often, how many minutes, who does it.
- Prioritization. A gain × feasibility matrix; we decide together where to start.
- Pilot workflow. We build a single process end-to-end and measure it. If the expected gain doesn’t show up, we don’t go any further.
- Rollout. If the pilot works, the other processes get lined up next.
- Monitoring and maintenance. Automations break as the systems they depend on change; monitoring and fixing them is ongoing work.
Frequently asked questions
Will our data leave the company?
That’s your decision, and we design the architecture around it. If data must not leave the organization, everything can be set up to run on your own servers. We state clearly in the project documentation which data goes where.
What happens if the AI makes the wrong decision?
In critical workflows we don’t let it make fully automatic decisions — the system prepares, a human approves. We decide together, based on risk, which steps of the automation run automatically and which need approval.
Can our existing software be integrated?
Almost any system with an API or webhook support can be connected. For closed systems, we look at what’s technically possible during discovery; if it isn’t possible, we say so.
How soon will we see results?
A pilot workflow covering a single process is usually the step that delivers results fastest. Scope and the number of systems to be integrated set the timeline; we give you a clear schedule after discovery.
Will we be dependent on you once the automation is in place?
We hand over documentation for the workflows we build, along with admin access to them. Your team can make simple changes on its own; we provide support for the complex ones.