Laya is an open-weight artificial-intelligence decision model released in September 2026 by Convai Innovations, a startup based in Kasaragod, Kerala, India, founded by Nandakishor M. Distributed under the Apache 2.0 license with weights on Hugging Face, Laya is positioned as the open, self-hostable counterpart to Jev, TypeSafe AI's closed "System One" decision model released the same month.
How it works
Laya is non-autoregressive: instead of generating text token by token like a large language model, it classifies. Given a piece of state (an email, a support ticket, an agent trace, a JSON object) and a list of typed questions with fixed answer sets, it returns the chosen answers with calibrated probabilities in a single forward pass. Because it produces no free-form text, there is nothing to hallucinate and no prose or JSON to parse; downstream code branches directly on the typed result and its confidence.
The main English checkpoint is built on a ModernBERT-large backbone with roughly 421 million parameters, small enough to run on modest local hardware. A multilingual variant covers more than 100 languages.
Performance claims
Convai reports a median (p50) latency of about 32.8 milliseconds on a single Tesla T4 GPU, which it compares to 236-276 ms measured for Jev's hosted API, a roughly 7.8x speed advantage on the vendor's own benchmark, at zero marginal cost when self-hosted. As with Jev's launch numbers, these figures come from the vendor's own evaluations and had limited independent verification in the weeks after release.
An important caveat acknowledged by the project itself: out of the box the base model scores near random on decision tasks - the headline accuracy numbers are achieved after fine-tuning on the target task. Laya is best understood as an open, efficient decision-model architecture you adapt to your workload, rather than a zero-shot drop-in.
Laya and Jev
Laya and Jev define an emerging category sometimes called System One models, after the fast, intuitive "System 1" of Daniel Kahneman's Thinking, Fast and Slow: models built for high-volume, low-latency classification, scoring, routing and next-step decisions that sit alongside generative Large language models rather than replacing them. The two differ mainly in distribution: Jev is a closed hosted API, while Laya's Apache-2.0 weights can be run locally (community runtimes exist for Node.js/TypeScript via ONNX Runtime), fine-tuned freely, and deployed without per-call costs.