AI in processes
Language models take on what is hard to describe with rules: non-standard documents, classification, questions about your data.
What gets automated
- Identifying the document type and recipient where rules fall short
- Extracting data from non-standard invoices
- Control: amounts above a threshold are not posted without human confirmation
- Asking your data questions in plain language via an MCP server
- Classifying messages and requests
- Translating and rewriting texts when needed
How it works
Where rules are not enough
We find the spots where a person currently decides by hand.
Model and checks
The model's answer goes through the same checks as all other data.
Trust threshold
What gets posted automatically and what waits for confirmation.
Oversight
A log of the model's decisions shows what it did and why.
FAQ
Does my data end up in public models?
Data is sent to the model provider via API only to process a specific request. What exactly is sent is agreed before launch.
What if the model makes a mistake?
AI output goes through the same checks as everything else: mismatches go to a person for review, and invoices above a threshold are not posted without confirmation.
Which models do you use?
Whatever fits the task: OpenAI models, Anthropic Claude and others via API. The model can be swapped without rebuilding the system.
Need similar automation?
Describe your process and we will estimate what can be handed over to a system.