AI at codebar
We're at the beginning of our AI journey – and open about what already runs: local open-source models on our own hardware.
Our local LLMs in action
For a few months now, we've been working our way into the topic, use case by use case. Here we keep track of which models we run – and how intensively.
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Tokens this month
Input
21'243
Output
0
18
Requests this month
Why local?
Customer data does not leave our infrastructure. That is the main reason we run open-source models ourselves instead of sending requests to a cloud provider. The trade-off: a little less performance at the top end – in exchange for full control over where data sits and what it costs.
We use AI where it measurably takes work off our hands: reading documents, sorting receipts, writing and reviewing code. Where it does not, we leave it alone. The usage figures show, unfiltered, how often that actually happens.
