THIRD_PARTY_NOTICES.md

Third-party notices

This release is an independent implementation of a public model interface. It uses code and design from two MIT-licensed projects, and it is not affiliated with, derived from, or endorsed by TypeSafe AI (the makers of "Jev").

trycua/cua — libs/cua-s1 (MIT)

• Source: https://github.com/trycua/cua/tree/main/libs/cua-s1
• Revision used: 9bbfa7d (the commit that links the Hugging Face artifacts)
• What we use: the tinyx architecture (cua_s1/model.py), the checkpoint format (cua_s1/checkpoint.py), the synthetic-data generator logic (cua_s1/synth.py), the training loop (training/train.py) and the evaluation metrics (evals/metrics.py). The files are vendored unmodified in the toolkit repository under vendor/, and the generated corpus follows the same row/dataset format.
• Copyright and licence text: see the upstream repository's LICENSE (MIT).

Our model is trained from scratch on our own Swedish synthetic corpus: it shares the architecture, the trainer and the data format, not any weights or data with Cua's release.

vinnylarouge/jevlike (MIT), via Cua's attribution

• Source: https://github.com/vinnylarouge/jevlike
• The option-attention head design (AttentionHead) and the byte-level collation shape used by the tinyx model originate in jevlike; Cua's model.py credits commit 94f5fd1 (MIT, Copyright 2026 Minimal Labs) and we keep that attribution intact in the vendored code.

What was NOT used

• No TypeSafe AI code, weights, data or API output. "Jev" and "System One" are TypeSafe AI's terms; this release is an independent model that implements a similar input/output contract.
• No real personal data. The training corpus is synthetic: fictional names, .invalid e-mail domains, locally generated personnummer-shaped identifiers that do not correspond to any individual, and invented organisations.