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  • QuickstartGet startedGet an API key, send one request with three questions, and branch your code on the typed answers. Plain HTTPS, no SDK to install.
  • POST /v1/decideAPI referenceAnswer typed questions about a state and optional images. One request, one buffered JSON response, one answer per question.
  • QuestionsConceptsQuestions say what to decide. Each one has a type that fixes the shape of its answer: a choice from your options, a score on your scale, a…
  • ConfidenceConceptsProbabilities are calibrated per question type, so a threshold means what it says.
  • ImagesConceptsSend images and text in the same request. The model reads printed and handwritten text, amounts, dates, objects and layout, and answers…
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Get API key
  • Guides
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Get started

  • Introduction
  • Quickstart
  • With coding agents
  • Examples

Concepts

  • State
  • Questions
  • Choice
  • Score
  • Truth
  • Number
  • Images
  • Confidence
  • Determinism

Models

  • DecisionNode-1.0
  • DecisionNode-1.0 Flash
  • Limits

Patterns

  • Confidence-gated routing
  • Fan-out
  • Guardrails
  • Control loopscomingcoming soon

API reference

  • POST/v1/decide
  • POST/v1/sessionscomingcoming soon
  • GET/v1/models
  • Errors
  • Rate limits

Pricing and billing

  • Pricing and billing

Policies

  • Responsible use

Migrate

  • Coming from a Jev-shaped API
  1. docs
  2. /
  3. Concepts

Score

A score question places the input on an ordered scale you define. It returns the expected level, the probability of every level and a confidence.

on this page4 sections
  1. Request
  2. Response
  3. Formulas
  4. Using a score
Score“How urgent is this?”
  1. 0.01
  2. 0.09
  3. 0.48
  4. 0.42
  1. 0 routine
  2. 1 today
  3. 2 urgent
  4. 3 critical

score 2.31 of 3confidence 0.47

Request#

JSON
{
  "urgency": {
    "type": "score",
    "instructions": "How urgent is this?",
    "criteria": ["routine", "today", "urgent", "critical"]
  }
}

criteria is an array of levels from lowest to highest, up to 10 of them (two or more make a scale). Level indexes start at 0 in the order you send them.

Response#

JSON
{
  "urgency": {
    "type": "score",
    "score": 2.31,
    "confidence": 0.47,
    "legend": {
      "0": "routine",
      "1": "today",
      "2": "urgent",
      "3": "critical"
    },
    "probabilities": { "0": 0.01, "1": 0.09, "2": 0.48, "3": 0.42 }
  }
}
scorenumber
The expected level index: the sum of each index times its probability.
probabilitiesobject
Level index to probability, in level order.
legendobject
Level index to your level text, exactly as sent.
confidencenumber
How tightly the probability sits around the most likely level, from 0 to 1.

Formulas#

score = sum(i · p_i)

confidence = 1 − E[|i − m|] / D(K)

D(K) = floor(K · K / 4) / K

i
the level index, from 0
p_i
the probability of level i
K
the number of levels
m
the most likely level, the lowest one on a tie
E[|i − m|]
the expected distance from m: sum(p_i · |i − m|)
D(K)
the largest that distance can be on K levels

Confidence is 1 when all the probability sits on one level. Probability on a level next to the most likely one costs little, and probability far from it costs a lot, so a scale split between two neighbours still reads as fairly sure. With two levels it equals the choice formula.

Worked example

score = 0 · 0.01 + 1 · 0.09

+ 2 · 0.48 + 3 · 0.42 = 2.31

m = 2 (urgent)

E = 0.01 · 2 + 0.09 · 1

+ 0.48 · 0 + 0.42 · 1 = 0.53

D(4) = floor(4 · 4 / 4) / 4 = 1

confidence = 1 − 0.53 / 1 = 0.47

These are the probabilities from the response above. A middling confidence with a high score is common and useful: the model is sure the ticket is at least urgent, and split between urgent and critical.

Using a score#

  • As a number: sort or prioritise by score directly. It is continuous, so 2.31 ranks above 2.12.
  • As a level: round(score) gives the nearest level; read its name from legend.
  • As a tail probability: add the probabilities of the levels you care about. Here the chance of urgent or worse is 0.48 + 0.42 = 0.90, which is often the gate you actually want.
previousChoicenextTruth

DecisionNode is built and run by Bynn Intelligence, Inc.

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on this page

  1. Request
  2. Response
  3. Formulas
  4. Using a score