Documents and invoices
Cost invoices, orders, contracts, delivery reports as PDFs or phone photos. AI reads the data, checks it against the order or the contractor and enters it into the accounting system. A person approves only what raises doubts.
AI automation
Every company has tasks that someone does a dozen times a day: retyping an invoice into the system, answering the same email, moving a form submission into the CRM, assembling a report from three spreadsheets. AI automation takes over these steps completely – even when the data arrives in a form a classic script can't read. The first working version is ready in 7–14 days.
Scope
Business automation doesn't start with "AI across the whole company", but with a single process that eats the most hours today. Below are the ones clients start with most often.
Cost invoices, orders, contracts, delivery reports as PDFs or phone photos. AI reads the data, checks it against the order or the contractor and enters it into the accounting system. A person approves only what raises doubts.
Classifying incoming messages, routing them to the right person, drafting replies based on the price list and customer history. Simple cases close on their own, harder ones reach the team already summarized.
Submissions from forms, chat and phone land in the CRM as completed cards: who is asking, about what, with what budget. The system assigns a salesperson, sets a task and reminds them to make contact before the lead goes cold.
A weekly summary of sales, stock or job completion, assembled from several sources and sent by email with a short comment: what changed and what to watch. No manual copying between spreadsheets.
Order status, rescheduling a visit, returns, complaints – in messengers and by phone. This is where automation meets AI chatbots and AI voice agents that perform actions in your systems instead of just answering.
Moving orders from email or a sales platform into the warehouse system, low-stock alerts, and in HR – onboarding a new employee: accounts, documents, a task list for the first week and answers to questions about the work rules.
Technology
Classic tools work great as long as the data is orderly. The problem is that in a small company it rarely is.
A robot repeats a person's clicks according to a rigid script. It works with fixed forms, but breaks when a supplier changes the invoice layout or a customer writes an email in their own way.
No-code platforms connect systems: when something happens in one, they trigger an action in another. We use them as the backbone of the workflow – they are transparent, cheap to maintain and easy to change when the process changes.
Where classic automation stops – the body of an email, a scanned document, a call note – we insert an LLM. It understands text, extracts data from it and makes simple decisions according to rules we set together.
How it works
First the process with the fastest payback, then the next ones. No automating everything at once.
We walk through how documents, inquiries and data flow today. We pick the processes where automation pays back fastest – usually 3–5 – with an estimate of the hours recovered. Details on the AI audit page.
We map the process step by step: where the data comes from, where the model decides, where a person does, what happens on an error. You get a schedule and a fixed subscription price.
We build the workflow, connect the systems and test on real documents and emails from recent weeks. The first version works after 7–14 days, at first in parallel with manual work, so you can compare results.
Every month we check which cases went to a person and why, refine the rules and add the next processes from the list. It's part of the subscription, not a separate project.
Honestly
Process automation costs money and needs maintenance. In a few situations it's better to stay with manual work – we say so on the first call.
FAQ
We bill by subscription, with no separate implementation fee. AI-based automation is included in the Standard package, while extensive integrations and closed systems on your own servers fall under the Maximum package. A PARP (Polish Agency for Enterprise Development) grant can cover up to 75% of costs. You'll find a sample calculation in the article how much AI implementation costs, and we write about funding on the page about PARP grants for AI.
The first working version is ready in 7–14 days. For the first few weeks the automation runs in parallel with manual work, so we can compare results and catch edge cases. Processes that need integration with several systems or a local LLM take longer – usually 4–8 weeks.
We work in line with GDPR, sign a data processing agreement and pass to the model only the data needed at a given step. If documents can't leave the company, we run a local LLM on a Mac Mini or a server with a graphics card on your network.
Usually yes, though it takes more work. We use file exports and imports, email inboxes, databases or interface automation where there's no other way. During the audit we check which option is the most stable for your system, and we tell you plainly if an integration would be too fragile.
It replaces tasks, not people. Retyping, sorting and copying data is taken over by the automation, while the team handles cases that need judgment and talks to customers. In practice, companies use the time they get back to handle more jobs without hiring another person.
With the one that repeats most often and has clear rules – often invoices, the email inbox or moving leads into the CRM. We set the order during the audit. We describe the broader picture of implementations on the page AI implementation in a company.
Let's start with one process
Free online consultation, 30 minutes. Tell us where your team loses the most time, and after the call you'll get a list of processes to automate, an estimate of savings and information about the PARP grant.