Laya: the open-source System 1 decision engine

**Multilingual, non-autoregressive System 1 decision engine.** Typed decisions over 100+ languages in a single forward pass — 33 ms — trained with reinforcement learning against strictly proper scoring rules (RLCD), with a router that picks the right checkpoint per request.

<div align="center">

[](https://colab.research.google.com/drive/15d4Yv__KHeHjshVb-6PRTfqVllxih2S3?usp=sharing)
[](https://pypi.org/project/laya/)
[](https://huggingface.co/convaiinnovations/laya)
[](https://huggingface.co/convaiinnovations/laya-multilingual)
[](https://huggingface.co/spaces/convaiinnovations/laya-demo)
[](https://dev.to/nandakishor_m_6cc0adfde9f/i-built-non-autoregressive-decision-models-a-year-ago-then-a-frontier-lab-called-it-a-18me)
[](https://www.buymeacoffee.com/nandakishorm)
[](https://opensource.org/licenses/Apache-2.0)

</div>

<p align="center">
  <img src="https://raw.githubusercontent.com/NandhaKishorM/laya/main/assets/laya_vs_jev_full.png" alt="Laya versus TypeSafe Jev: accuracy on shared public datasets, every application workflow, all 51 languages, speed, calibration, and the cost of not preloading" width="100%" />
</p>

Laya evaluates typed questions (`choice`, `score`, `noul`) over any state (text, email, ticket or JSON document) in **a single forward pass** — 33 ms for one question, 7.2 ms/question batched, measured on a T4. No text generation, so nothing to parse and nothing to hallucinate.

Three checkpoints, and a `Router` that picks between them per request:

| | encoder | params | context | use it for |
|---|---|---|---|---|
| [`laya`](https://huggingface.co/convaiinnovations/laya) | ModernBERT-large | 421M | 512 | English |
| [`laya-multilingual`](https://huggingface.co/convaiinnovations/laya-multilingual) | mmBERT-base | 322M | 1024 | 100+ languages, 2x fast