the short answer
Convai Innovations publishes Laya as an Apache 2.0 family you can run locally. Its Python runtime takes state plus Choice, Score or Noul questions, and it offers separate English and multilingual checkpoints. Jev is TypeSafe’s hosted model. Laya’s language and speed figures come from its publisher. For a multilingual ticket queue, test the exact languages and scripts you receive, then count errors, calibration, hardware use and review cost.
- Publisher
- Convai Innovations, independent of TypeSafe AI
- Distribution
- Apache 2.0 model card and public Python runtime
- Laya checkpoints
- English, multilingual and typed-decisions variants
- Jev deployment
- Hosted TypeSafe model; provider paths vary
- Benchmark status
- Project-reported results; test on target-language labels
Which Checkpoint Handled the Ticket?
Laya ships English, multilingual and task-adapted typed-decision checkpoints. Its Router chooses one by language. Record that choice on every test case, because an overall multilingual score can hide a weak script or a routing error. Laya’s own card flags long documents and some language slices as weak spots.
The Jev model card describes a separate hosted service. Running Laya locally moves data and operating cost into your own infrastructure, along with checkpoint updates and serving failures. That may be a good trade for your traffic. Measure it with your actual language mix.
Use the Same Multilingual Triage Example
For every ticket, keep the language, chosen checkpoint, input length, full distribution and reviewer label. Give Jev and Laya the same tickets. An English-only Jev run against a multilingual Laya run would tell you about the sample, not the model. The language guide shows how to report the slices.
| Test slice | Expected review question |
|---|---|
| English ticket | Which team resolves the first blocker? |
| Hindi or Spanish ticket | Does the same rubric survive translation and code switching? |
| Mixed-language ticket | Does routing choose the intended checkpoint and preserve the right label? |
| Long thread | Does decisive evidence survive truncation and irrelevant history? |
Separate Interface, Deployment and Quality
| Question | Evidence now | What to measure |
|---|---|---|
| Can it run locally? | Laya publishes checkpoints and runtime; official Jev weights are not public | Memory, throughput, operations and license |
| Can it answer typed questions? | Both document bounded question interfaces | Conformance and failure behavior |
| Is it multilingual? | Laya publishes a multilingual checkpoint; Jev says English is strongest | Accuracy and calibration per target language |
| Which is faster or better? | No universal independent result established | Matched hardware/provider, labels and action risk |
How to Benchmark Jev and Laya
The Laya card’s language and speed numbers came from its own setup. Record your hardware and per-language errors in the paired report. Add the long and adversarial state cases in Jev limitations to the fixture set.
- Choose one decision and freeze labels grouped by customer and language.
- Pin the Laya checkpoint and runtime, plus Jev model and provider.
- Run identical evidence and answer definitions while retaining native outputs.
- Report class errors, calibration, review coverage, truncation, latency and all failures per language.
- Shadow the intended production route before changing any automated action.
FAQ
Is Laya made by TypeSafe AI?
No. Laya is published by Convai Innovations as an independent decision-model family.
Can Laya replace Jev without testing?
A matching question type lets you reuse a fixture. You still need a local serving test, labeled accuracy, calibration and new review thresholds for Laya.
Does Laya support languages beyond English?
Its publisher provides a multilingual checkpoint and reports tests across many languages. Validate the languages and scripts your workflow actually receives.
Sources
Checked against the sources below on October 2, 2026. Model versions, prices and limits change.
- Convai Innovations: Laya model card
- Laya: official source and runtime
- TypeSafe AI: Jev primitives
- TypeSafe AI: Jev models
Change note: Added an evidence-bounded comparison of Laya’s official model and runtime.