AI on demand: convaiinnovations/laya

System One Model - Introduction

System One models such as Laya assess text and return structured decisions in a single forward pass. They support three question types:

• choice
  • selects a category, such as the department responsible for a ticket

• noul
  • returns the probability that a statement is true, such as whether a customer requests a refund.

• score
  • assesses text against an ordered scale, such as urgency from low to critical.

These models suit classification, routing, and decision support. They do not generate conversational answers or explanations, and their predictions can be wrong. Reported probabilities require evaluation on representative data before using them for consequential automation.

Our service uses Laya’s multilingual checkpoint with a fixed 4,096-token input limit.

System One Model - Usage

To use a System One model set your stoney key

STONEY_KEY=sk-....

System One Model - Usage choice

Use this category for example to route a request to a department.

Input:

curl --fail-with-body -sS \
  https://llm.stoney-cloud.com/v1/systemone \
  -H "apikey: $STONEY_KEY" \
  -H 'Content-Type: application/json' \
  --data-binary '{
    "model": "convaiinnovations/laya",
    "state": {
      "document": "Meine Rechnung wurde zweimal belastet. Bitte prüfen Sie die doppelte Zahlung."
    },
    "questions": {
      "department": {
        "type": "choice",
        "instructions": "Which department should handle this request?",
        "criteria": {
          "technical": "Application errors and login problems",
          "billing": "Invoices, payments and duplicate charges",
          "support": "General customer support and newsletter preferences"
        }
      }
    }
  }' | jq .

Output:

{
  "model": "convaiinnovations/laya",
  "answers": {
    "department": {
      "type": "choice",
      "choice": "billing",
      "probabilities": {
        "technical": 0.0,
        "billing": 0.9999,
        "support": 0.0
      },
      "confidence": 0.9994,
      "answer_confidence": 0.9999,
      "action": {
        "act_probability": 1.0
      }
    }
  },
  "usage": {
    "input_tokens": 61,
    "output_tokens": 0,
    "state_tokens": 20,
    "state_tokens_dropped": 0,
    "truncated": false,
    "truncated_questions": [],
    "prompt_tokens": 61,
    "completion_tokens": 0
  },
  "routing": {
    "model": "multilingual",
    "repo": "convaiinnovations/laya/multilingual",
    "reason": "explicit model='multilingual'",
    "detection": null,
    "workflow": null
  }
}

System One Model - Usage noul

Use noul to check a statement, for example to detect if customer explicitly requests a refund.

Input:

curl --fail-with-body -sS \
  https://llm.stoney-cloud.com/v1/systemone \
  -H "apikey: $STONEY_KEY" \
  -H 'Content-Type: application/json' \
  --data-binary '{
    "model": "convaiinnovations/laya",
    "state": {
      "document": "Meine Rechnung wurde zweimal belastet. Bitte erstatten Sie mir die zweite Zahlung zurück."
    },
    "questions": {
      "refund_requested": {
        "type": "noul",
        "instructions": "Does the customer explicitly request a refund?",
        "criteria": {
          "true": "The customer explicitly asks for money to be returned.",
          "false": "The customer does not ask for money to be returned."
        }
      }
    }
  }' | jq .

Output:

{
  "model": "convaiinnovations/laya",
  "answers": {
    "refund_requested": {
      "type": "noul",
      "noul": 0.9697,
      "confidence": 0.9697,
      "answer_confidence": 0.9697,
      "action": {
        "act_probability": 1.0
      }
    }
  },
  "usage": {
    "input_tokens": 65,
    "output_tokens": 0,
    "state_tokens": 22,
    "state_tokens_dropped": 0,
    "truncated": false,
    "truncated_questions": [],
    "prompt_tokens": 65,
    "completion_tokens": 0
  },
  "routing": {
    "model": "multilingual",
    "repo": "convaiinnovations/laya/multilingual",
    "reason": "explicit model='multilingual'",
    "detection": null,
    "workflow": null
  }
}

System One Model - Usage score

Use score to for example estimate the urgency of a support request. Arrange criteria from lowest to highest.

Input:

curl --fail-with-body -sS \
  https://llm.stoney-cloud.com/v1/systemone \
  -H "apikey: $STONEY_KEY" \
  -H 'Content-Type: application/json' \
  --data-binary '{
    "model": "convaiinnovations/laya",
    "state": {
      "document": "Unser gesamtes Produktionssystem ist ausgefallen. Alle Kunden sind betroffen und können keine Bestellungen aufgeben. Wir benötigen sofort Hilfe."
    },
    "questions": {
      "urgency": {
        "type": "score",
        "instructions": "How urgent is this support request?",
        "criteria": [
          "Not urgent: informational request with no operational impact",
          "Low urgency: minor inconvenience with a workaround",
          "Moderate urgency: partial disruption affecting some users",
          "High urgency: major disruption requiring prompt attention",
          "Critical urgency: complete production outage affecting all customers"
        ]
      }
    }
  }' | jq .

Output:

{
  "model": "convaiinnovations/laya",
  "answers": {
    "urgency": {
      "type": "score",
      "score": 3.987,
      "legend": {
        "0": "Not urgent: informational request with no operational impact",
        "1": "Low urgency: minor inconvenience with a workaround",
        "2": "Moderate urgency: partial disruption affecting some users",
        "3": "High urgency: major disruption requiring prompt attention",
        "4": "Critical urgency: complete production outage affecting all customers"
      },
      "probabilities": {
        "0": 0.0003,
        "1": 0.0016,
        "2": 0.0012,
        "3": 0.0044,
        "4": 0.9924
      },
      "confidence": 0.9673,
      "answer_confidence": 0.9924,
      "action": {
        "act_probability": 1.0
      }
    }
  },
  "usage": {
    "input_tokens": 112,
    "output_tokens": 0,
    "state_tokens": 31,
    "state_tokens_dropped": 0,
    "truncated": false,
    "truncated_questions": [],
    "prompt_tokens": 112,
    "completion_tokens": 0
  },
  "routing": {
    "model": "multilingual",
    "repo": "convaiinnovations/laya/multilingual",
    "reason": "explicit model='multilingual'",
    "detection": null,
    "workflow": null
  }
}