convaiinnovations/laya-demo

Space

Laya Demo

17

9 commits

1 linked in READMEs

updated Sep 18, 2026

See the code
gradio

README

Laya Demo

Laya is a fast System 1 decision engine: send a state and typed questions, get typed answers with probabilities and a confidence score. It never generates text, so there is nothing to parse and nothing to hallucinate.

typequestionanswer
choicewhich of these options?the option, a probability per option, confidence
scorewhere on this rubric?a position along your levels, probabilities, confidence
noulis this true?the probability that it is

The tabs are the patterns people use most: support triage, email and phishing, LLM guardrails, RAG passage filtering, moderation, model routing, and a free-form playground. Every tab asks all of its questions in one pass and then decides what to do with plain code: the thresholds live in the app, not in the model.

This is a preview checkpoint (421M parameters, trained with pure reinforcement learning against proper scoring rules on public datasets). It is strong on routing, classification, moderation and guardrails, weaker on rubric scores, and it saw no email data, so treat the email tab as generalisation rather than a trained skill.

Built by Convai Innovations.

Contributors

convaiinnovations/laya-demo

Space

Laya Demo

17

9 commits

1 linked in READMEs

updated Sep 18, 2026

See the code
gradio

README

Laya Demo

Laya is a fast System 1 decision engine: send a state and typed questions, get typed answers with probabilities and a confidence score. It never generates text, so there is nothing to parse and nothing to hallucinate.

typequestionanswer
choicewhich of these options?the option, a probability per option, confidence
scorewhere on this rubric?a position along your levels, probabilities, confidence
noulis this true?the probability that it is

The tabs are the patterns people use most: support triage, email and phishing, LLM guardrails, RAG passage filtering, moderation, model routing, and a free-form playground. Every tab asks all of its questions in one pass and then decides what to do with plain code: the thresholds live in the app, not in the model.

This is a preview checkpoint (421M parameters, trained with pure reinforcement learning against proper scoring rules on public datasets). It is strong on routing, classification, moderation and guardrails, weaker on rubric scores, and it saw no email data, so treat the email tab as generalisation rather than a trained skill.

Built by Convai Innovations.

Contributors