AI automation for businesses: from manual work to flows that run themselves

It depends on how many variants of the task have to be handled, how open your systems are and how much human review you want. We always start with a small prototype against your real data, so you know within two weeks whether it holds. Then you get a fixed price for the full solution, with the ongoing model cost per run quoted separately.

A chatbot is a window where a person types questions. AI automation is the model working inside your systems without anyone asking: reading the invoice that arrived, sorting the email, writing the draft. The chatbot needs someone sitting at it. The automation saves time precisely because nobody has to.

By never letting it make decisions that cannot be checked. Every answer is stored with its inputs, the model is forced to cite a source when answering questions, and at first a person reviews everything. We measure accuracy in the prototype against your own examples before building anything, and in production we track it week by week.

With the model provider we choose together, through their business API where data is contractually not used for training. For sensitive data we choose EU regions or a model that runs in your own environment. You get a clear picture of the data flow before we build, and we build so the provider can be swapped.

Things done often, by several people, where the input is text or documents and where an error can be caught before it costs anything. Invoices, incoming tickets, quote drafts and summaries are common first steps. We help you pick one task, not ten, and measure how long it takes today.

Yes, it is one of the most common first steps. The model reads supplier invoices in any format, extracts supplier, amount, VAT and references, matches against the order or contract and leaves a suggested booking in the finance system. Unlike template-based capture it handles suppliers it has never seen before. Finance only reviews the exceptions.

An AI agent is a language model allowed to carry out several steps on its own: read, look things up in your systems, choose the next step and write back. It is needed when a process varies a lot from case to case. If the steps are always the same, a fixed flow where AI only interprets the input is enough, and it is both cheaper and easier to trust. We propose the simplest thing that solves the task.

The prototype against your data takes one to two weeks. A finished solution built into your system with a review flow normally takes a few weeks to a couple of months depending on the integrations. You see results every week and can stop after the prototype if the numbers do not hold.

Usually not. AI automation works best built into the systems you already use, connected through their APIs. If a system lacks an API we build the route first. If the problem is that none of your systems does what you need, that is a custom software project, and we say so.

Yes. A common first engagement is to go through the business, list the tasks that take the most time and assess which suit AI, which are solved by ordinary integration and which should be left alone. You get a prioritised list with estimated savings, not a presentation about AI in general.