Laya

GPU · public beta

A hosted instance of Laya, an open-source non-autoregressive decision model. Send it a state (text, email, ticket, JSON) plus typed questions and get back typed answers with calibrated probabilities in a single forward pass — no text generation, nothing to parse.

Laya is an open-source alternative to Jev, the proprietary "System One" model: the same idea (choice, score and noul questions with calibrated confidence, evaluated in parallel against one state), but Apache-2.0 weights you can self-host, no per-token cost and no data leaving your infrastructure.

Laya vs Jev

Jev Laya (this endpoint)
Latency (1 question) ~100 ms typical (70–500 ms) ~35–40 ms on GPU; 10 questions batched in ~160 ms
Question types choice, score, noul Same three, same request/response shape
Architecture Undisclosed ModernBERT-large / mmBERT encoder + decision head, 322–421M params
Calibration RLCD, details not public RLCD with published proper-scoring-rule reward; calibration curves in repo
Languages Not published English model + 100-language model, auto-routed per request
Limits Up to 255 options per choice 512 tokens/question (English), 1,024 (multilingual)

Full benchmarks and calibration plots: Laya README · model card.

Endpoint

POST https://laya.pensero.ai/predict   (alias: https://jev.pensero.ai/predict)
Content-Type: application/json
Field Type Description
state object | string What to decide about.
questions object Map of question id → {type, instructions, criteria}. Types: choice, score, noul (boolean).
model string, optional english, multilingual or typed-decisions. Auto-routed by language when omitted.

Example

curl -s https://laya.pensero.ai/predict \
  -H 'content-type: application/json' \
  -d '{
    "state": {"subject": "Duplicate charge on invoice #4411",
              "body": "We were billed twice for March. Refund today or we cancel."},
    "questions": {
      "department": {"type": "choice", "instructions": "Which department should handle this?",
                     "criteria": {"billing": "invoices, refunds", "technical": "bugs, outages", "sales": "pricing"}},
      "urgency":    {"type": "score", "instructions": "How urgent is this?",
                     "criteria": ["not urgent", "soon", "critical"]},
      "churn_risk": {"type": "noul", "instructions": "Does the user threaten to cancel?"}
    }
  }'

Response: answers.department.choice, per-option probabilities, a calibrated confidence, and routing metadata explaining which checkpoint was used.

Limits

Interactive OpenAPI docs: /docs