AI automation in the office: less typing, searching and forwarding
Much of office work consists of typing, searching, matching and forwarding. With AI these steps can be joined into one workflow, from the mailbox through the ERP to accounting. Sortia Labs automates such processes for companies in Munich and across Germany, with clear rules and an approval step where it matters.
- AI automation
- Process automation
- Office automation
- Workflow automation with AI
- Python automation
Workflows that AI can automate
Bank reconciliation
Statements in camt.053, MT940 or CSV are imported and matched to open invoices by amount, date, IBAN and payment reference. AI helps where the reference is incomplete or written freely.
Moving data between systems
Orders from the web shop into the ERP, contacts from forms into the CRM, hours from spreadsheets into billing. Where an interface is missing, the AI reads e-mails or PDFs and fills in the fields.
Keeping master data current
Changes in e-mails, forms or letters, such as a new address or contact person, are recognised and prepared as a proposed change to the master data. Nothing is applied until your team confirms it.
Reports and summaries
Weekly figures from several sources, summaries of long ticket threads or an overview of open items, delivered as an e-mail, a PDF or a message in your team channel at a set time.
Filing and archive
Incoming documents get a meaningful name, date and sender and land in the right folder of your document management. Duplicate files are recognised by content instead of being filed twice.
How we automate a workflow
- 1
Map the workflow
We look over the shoulders of your team and count: how often does the task occur, how long does it take, where do errors happen? That gives the expected savings.
- 2
Rule or AI
Each step gets the right tool. What a fixed rule can solve is solved by a rule, because it is cheaper and predictable. AI is used where text has to be understood.
- 3
Build and connect
We build the workflow with Python, FastAPI and Docker, connect it to your systems and set up approvals. Before going live it runs alongside your current process for a while.
- 4
Measure and operate
Monitoring, error alerts and a monthly report on cases, savings and exceptions. You see whether the automation pays off, and we see where it can improve.
Software we build and run ourselves.
Questions about AI automation
What is the difference between RPA and AI automation?
RPA clicks through user interfaces like a person and follows fixed rules; when a screen changes, the workflow often breaks. AI automation works through interfaces and also understands unstructured content such as e-mails or PDFs. The two can be combined when an old system has no interface.
Which processes are good to start with?
Frequent, similar tasks with a clear result: invoice intake, bank reconciliation, data transfer between systems, recurring reports. Rare special cases and decisions that need a lot of experience are poor candidates for a start. The AI opportunity assessment ranks your candidates by effort and savings.
What happens if the automation fails?
Errors are reported, and unprocessed cases wait in a queue until they are caught up or handled by hand. Your team can therefore work on a case as before while a system is unavailable. Monitoring shows us the fault so that we can fix it.
Do we have to replace our existing software?
Usually not. The automation sits on top of your existing systems and uses their interfaces, file exports or mailboxes. If an application offers no access at all, we talk openly about modernising it step by step.
Read on.
Which workflow ties up too much of your time?
Describe it in a few sentences. You get an assessment of which steps suit rules, which suit AI and which are better left alone.