Insurance Intelligence API

Classify text with structured, versioned results. The Insurance Intelligence analyzer classifies text against 200 indicators in 4 groups across 40 supported languages.

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

Try it live Request access

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": "We staged the collision in the parking lot and agreed to split the payout three ways.",
    "language": "en",
    "analyzers": [
        "insurance"
    ]
}'

Example response:

{
    "language": "en",
    "language_source": "declared",
    "signals": [
        {
            "analyzer": "insurance",
            "code": "claim_fraud",
            "label": "Claim Fraud",
            "score": 0.93,
            "level": "category"
        },
        {
            "analyzer": "insurance",
            "code": "fraud_staged_accident",
            "label": "Staged or deliberate auto accident",
            "score": 0.91,
            "level": "label",
            "parent": "claim_fraud"
        },
        {
            "analyzer": "insurance",
            "code": "fraud_swoop_squat",
            "label": "Swoop and squat or forced collision scheme",
            "score": 0.88,
            "level": "label",
            "parent": "claim_fraud"
        }
    ],
    "meta": {
        "analyzers": [
            {
                "name": "insurance",
                "status": "completed",
                "applicability": "analyzable",
                "assessment": "signals_detected",
                "signal_count": 3,
                "billed": true
            }
        ]
    },
    "usage": {
        "analyzer_runs": 1
    },
    "verification": {
        "configuration": "sqcfg_GFAWTERR",
        "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 insurance.

Request

{
    "text": "We staged the collision in the parking lot and agreed to split the payout three ways.",
    "language": "en",
    "analyzers": [
        "insurance"
    ]
}

Parameters

Parameter	Type	Required	Default	Description
text	string	Yes	-	Text to analyze
language	string	No	"en"	Supported language code
analyzers	string[]	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/insurance

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
analyzer	string	Analyzer that produced this signal
code	string	Stable machine identifier - immutable across API versions; use for storage and cross-referencing
label	string	Human-readable display name
score	float	Signal-match strength (0.0-1.0)
level	string	"category" or "label"
parent	string	Parent 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

Insurance Intelligence currently supports 40 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
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 Insurance Intelligence taxonomy contains 4 groups and 200 indicators. Representative entries are shown publicly - the complete taxonomy is available to customers after request access .

Browse all 4 groups Search all 200 indicators

1

Claim Type

claim_type

50 indicators

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

2

Claim Fraud

claim_fraud

60 indicators

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

3

Claim Process

claim_process

40 indicators

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

4

Claim Details

claim_details

50 indicators

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

Reading Insurance Intelligence output

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

Intended task

Classify claim narratives into documented claim types and fraud-pattern signal groups - for routing and SIU review.

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 "insurance"; 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.
Analyzes the narrative text only - policy terms, claim history, and evidence files are not inputs.

Ordinary positive

“My parked car was hit overnight. The other driver left a note with their plate number and insurer.”

claim_type_auto very high

claim_third_party_claimant high

Safe inference: The narrative classifies as an auto claim with a third-party element - route it to the auto queue with subrogation flagged.

Confusing negative · Quotation

“The claimant's own witness said "we agreed to split the payout" - see the attached statement.”

What happens: Fraud-pattern signals can fire on the quoted statement. The signal flags that the language matches a documented fraud pattern - it does not weigh whose words they are or whether the statement is credible.

Why it's tricky: Claim files are full of quoted speech - witness statements, adjuster notes, reported conversations. A fraud-pattern signal on a narrative is a review trigger, never a finding: route it to your SIU, and let investigators weigh the evidence.

What you can safely infer

Which documented claim types and fraud-pattern groups the narrative matched.
That the same narrative on the same pinned configuration classifies identically - the receipt supports dispute review.

What you must not infer

✕That fraud occurred or that the claimant lied - fraud signals route review, they do not determine wrongdoing.
✕Coverage, liability, or payout decisions - those stay with your adjusters and policy terms.
✕That a claim with no fraud signal is verified legitimate - a missing signal is "not detected," never "cleared."

Boundary: Fraud signals are not proof of wrongdoing. They flag language consistent with documented fraud patterns so a reviewer looks - the determination stays with your SIU and your process.

Signal reference Evaluation evidence Understanding signals API reference Evaluate on your data

Insurance Intelligence API

Make your first request

Endpoint

Related endpoints

Response fields

Important behavior

Supported languages

Taxonomy

Reading Insurance Intelligence output

Next steps