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Wellness Intelligence API

Classify text with structured, versioned results. The Wellness Intelligence analyzer classifies text against 200 indicators in 4 groups across 41 supported languages.

Use the returned groups, indicators, confidence values, and version metadata in your own triage and review workflows.

POST /v1/analyze · REST · JSON · Bearer authentication

Make your first request

curl -X POST https://sentiqra.tech/v1/analyze \
  -H "Authorization: Bearer $SENTIQRA_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "text": "I haven't slept more than four hours a night all week and I can't seem to wind down.",
    "language": "en",
    "analyzers": [
        "wellness"
    ]
}'

Example response:

{
    "language": "en",
    "language_source": "declared",
    "signals": [
        {
            "analyzer": "wellness",
            "code": "physical_health",
            "label": "Physical Health",
            "score": 0.93,
            "level": "category"
        },
        {
            "analyzer": "wellness",
            "code": "sleep_quality_poor",
            "label": "Poor sleep quality",
            "score": 0.91,
            "level": "label",
            "parent": "physical_health"
        },
        {
            "analyzer": "wellness",
            "code": "difficulty_falling_asleep",
            "label": "Difficulty falling asleep",
            "score": 0.88,
            "level": "label",
            "parent": "physical_health"
        }
    ],
    "meta": {
        "analyzers": [
            {
                "name": "wellness",
                "status": "completed",
                "applicability": "analyzable",
                "assessment": "signals_detected",
                "signal_count": 3,
                "billed": true
            }
        ]
    },
    "usage": {
        "analyzer_runs": 1
    },
    "verification": {
        "configuration": "sqcfg_WJ0XM1NX",
        "fingerprint": "fp_8a72...19f",
        "input_commitment": "ic_31bd...a42",
        "signature": "sig_ed25519_4c1f...e2a",
        "key_id": "edk_af4f218e"
    }
}

Don't have an API key? Generate one from the API Keys page in your dashboard.

Endpoint

POST /v1/analyze

Analyzes submitted text and returns structured signals with scores and a verification receipt. Select this analyzer via the analyzers parameter with ID wellness.

Request

{
    "text": "I haven't slept more than four hours a night all week and I can't seem to wind down.",
    "language": "en",
    "analyzers": [
        "wellness"
    ]
}

Parameters

Parameter Type Required Default Description
textstringYes-Text to analyze
languagestringNo"en"Supported language code
analyzersstring[]Yes-1–2 analyzer slugs to run (never defaults to all)

Related endpoints

GET /v1/meta/domains

Lists all analyzers with identifiers, status, and endpoints - no authentication required. Send a Bearer API key for taxonomy size and language counts.

GET /v1/meta/domains/wellness

Identifier, availability, and endpoint for this analyzer. Send a Bearer API key for taxonomy summary and supported languages.

GET /v1/account/usage

Current-period usage and quota for your API key. Requires authentication.

Response fields

Field Type Description
analyzerstringAnalyzer that produced this signal
codestringStable machine identifier - immutable across API versions; use for storage and cross-referencing
labelstringHuman-readable display name
scorefloatSignal-match strength (0.0-1.0)
levelstring"category" or "label"
parentstringParent category code (label-level only)

Important behavior

Determinism

For the same normalized input evaluated against the same pinned configuration and output profile, Sentiqra returns the same canonical signals. Version changes are explicit.

Confidence

A score expresses signal-match strength under a particular analyzer configuration. It is not a probability that the signal or a downstream action is correct. Validate action thresholds on representative labeled data.

Privacy

Submitted text is processed in memory and not retained. See data handling for exact retention behavior.

Limits

Character limit, RPS, and monthly quota depend on your plan. See pricing for current limits.

Supported languages

Wellness Intelligence currently supports 41 languages.

Code Language Status
ar Arabic Production
arz Egyptian Arabic Production
be Belarusian Production
bg Bulgarian Production
bn Bengali Production
cs Czech Production
da Danish Production
de German Production
el Greek Production
en English Production
es Spanish Production
fi Finnish Production
fr French Production
ha Hausa Production
hi Hindi Production
hr Croatian Production
hu Hungarian Production
id Indonesian Production
it Italian Production
ja Japanese Production
ko Korean Production
lt Lithuanian Production
mr Marathi Production
nl Dutch Production
no Norwegian Production
pcm Nigerian Pidgin Production
pl Polish Production
pt Portuguese Production
ro Romanian Production
ru Russian Production
sk Slovak Production
sr Serbian Production
sv Swedish Production
sw Swahili Production
ta Tamil Production
te Telugu Production
tr Turkish Production
uk Ukrainian Production
ur Urdu Production
vi Vietnamese Production
zh Chinese Production

All languages this detector supports are enabled on every plan. Custom or restricted arrangements may scope language access - check the dashboard or GET /v1/account/entitlements for account-specific availability.

Detector does not support language → 400 unsupported_language
Detector supports language but the account is not entitled (restricted/custom arrangements only - GA plans include all supported languages) → 403 language_not_in_plan

View language coverage and benchmarks →

Taxonomy

The Wellness Intelligence taxonomy contains 4 groups and 200 indicators. Representative entries are shown publicly - the complete taxonomy is available to customers after request access .

1

Mental Emotional

mental_emotional

60 indicators

The complete signal list is available to customers. Request access to view it.

2

Physical Health

physical_health

70 indicators

The complete signal list is available to customers. Request access to view it.

3

Social Support

social_support

20 indicators

The complete signal list is available to customers. Request access to view it.

4

Tools Productivity

tools_productivity

50 indicators

The complete signal list is available to customers. Request access to view it.

Reading Wellness Intelligence output

What you can safely infer from a result - and what you must not.

Intended task

Turn check-in and journal text into documented wellbeing signals - sleep, stress, coping, help-seeking - that a wellness product can route on.

Input requirements

  • text - the only field analyzed; up to 4,096 Unicode code points. Over the limit is rejected with input_too_long, never truncated.
  • language - must be a language this analyzer supports. Unsupported codes are rejected with 400 unsupported_language, never analyzed as a different language.
  • analyzers - include "wellness"; up to 2 analyzers per request, one billed run each.
  • No context beyond text - no user IDs, history, profiles, or attachments are read or inferred.
  • Very short check-ins carry little signal - "tired" alone can return a weak or empty result.

Ordinary positive

“I have slept badly three nights running and keep skipping meals - I feel completely drained.”

sleep_recovery very high
stress_balance high
nutrition_hydration medium

Safe inference: The check-in touches sleep, stress, and nutrition - enough to route a recovery-focused suggestion rather than a generic tip.

Confusing negative · Insufficient context

“My doctor said my results were normal but I still feel exhausted.”

What happens: Wellbeing signals can fire on the fatigue language - but the text also mentions a clinical finding the analyzer cannot evaluate. The signal describes wellbeing language in the text; it does not weigh medical content.

Why it's tricky: Wellness text often brushes against clinical claims. A sleep or stress signal is a content-routing hint - it is never a diagnosis, and concerning content should follow your own escalation policy rather than the signal alone.

What you can safely infer

  • Which documented wellbeing topics the text touches, and at what strength.
  • That results are reproducible - the same check-in on the same pinned configuration returns the same signals.

What you must not infer

  • ✕A diagnosis or clinical status - wellness signals are not medical assessment.
  • ✕That a user is at risk, or safe - escalation decisions belong to your own safety policy and human review.
  • ✕That flat or empty results mean the user is well - thin text is thin evidence, not a clean bill of health.

Boundary: Wellness signals are not diagnoses. They describe wellbeing language in the text for product routing - suggestions, check-ins, content matching - never a clinical assessment.

Next steps