Market Intelligence API
Turn financial text into structured event signals. The Market Intelligence API classifies submitted text against 200 indicators across 20 event groups in 8 supported languages.
Use structured event signals in research, surveillance, risk, and systematic workflows.
POST /v1/analyze · analyzer ID: finance · REST · JSON · Bearer authentication
Scope
Sentiqra classifies the text you submit. It does not provide market prices, order books, trading volume, portfolio positions, return forecasts, or trade execution.
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": "The company announced an all-cash acquisition expected to close next quarter.",
"language": "en",
"analyzers": [
"finance"
]
}'
Example response:
{
"language": "en",
"language_source": "declared",
"signals": [
{
"analyzer": "finance",
"code": "corporate_events",
"label": "Corporate Events",
"score": 0.92,
"level": "category"
},
{
"analyzer": "finance",
"code": "merger_acquisition",
"label": "Merger & Acquisition",
"score": 0.9,
"level": "label",
"parent": "corporate_events"
}
],
"meta": {
"analyzers": [
{
"name": "finance",
"status": "completed",
"applicability": "analyzable",
"assessment": "signals_detected",
"signal_count": 2,
"billed": true
}
]
},
"usage": {
"analyzer_runs": 1
},
"verification": {
"configuration": "sqcfg_TQ2ER9EK",
"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
/v1/analyze
Classifies financial text and returns ranked event groups and indicators.
Request
{
"text": "The company announced an all-cash acquisition expected to close next quarter.",
"language": "en",
"analyzers": [
"finance"
]
}
Parameters
| Parameter | Type | Required | Default | Description |
|---|---|---|---|---|
| text | string | Yes | - | Financial text to classify |
| language | string | No | "en" | Language code supported by the Market Intelligence detector (en, zh, ja, de, fr, it, hi, ko) |
Advanced parameters →
Related endpoints
GET /v1/meta/domains/finance
Identifier, availability, and endpoint for this analyzer. Send a Bearer API key for taxonomy summary and supported languages.
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.
What the API can infer from text
Sentiqra is designed to classify explicit or semantically expressed financial events such as:
From supplied text
- • Earnings beats and misses
- • Guidance changes
- • M&A announcements
- • Executive changes
- • Dividends and capital raises
- • Regulatory investigations
- • Credit distress
- • Sanctions and geopolitical events
- • Supply disruptions
- • Official confirmations and denials
Requires external / stateful data
- • Unusual trading volume
- • ETF inflow or outflow spikes
- • Price breakouts
- • Volatility changes
- • Yield-curve moves
- • Correlation breaks
- • Forced liquidations
- • Rumor velocity
- • News novelty
If the submitted text reports one of these events, Sentiqra can classify the reported event. To establish that it actually occurred, combine the classification with your own market data, source evidence, or stateful analytics.
Response structure
groups
High-level event categories (level: "category").
{
"analyzer": "finance",
"code": "corporate_events",
"label": "Corporate Events",
"score": 0.92,
"level": "category"
}
signals
More specific indicators within each group (level: "label").
{
"analyzer": "finance",
"code": "merger_acquisition",
"label": "Merger & Acquisition",
"score": 0.9,
"level": "label",
"parent": "corporate_events"
}
parent
Category slug this label-level signal belongs to. Dotted form is group.label - e.g. corporate_events.merger_acquisition means merger_acquisition sits under corporate_events.
| Field | Type | Description |
|---|---|---|
| code | string | Stable machine identifier |
| label | string | Human-readable display name |
| parent | string | Parent category code (label-level only) |
| score | float | Signal-match strength (0.0–1.0) |
Signal scores
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.
Paid API keys receive the continuous score (profile full.v1); anonymous, playground, demo, and free-tier responses return banded scores with a confidence band (profile reduced.v1). See Understanding signals for the profile and band table.
It does not represent:
- • Expected asset return
- • Probability a trade will be profitable
- • Materiality to a particular security
- • Confidence that a downstream action is appropriate
Calibrate thresholds by event type and workflow using your own labeled evaluation set.
Use event classifications as one feature in customer-owned research, risk, or systematic models. Your models determine the trading or risk decision. Sentiqra supplies structured event evidence.
200 indicators across 20 event groups
The Market Intelligence taxonomy includes:
Deterministic classification
For the same normalized input evaluated against the same supported pinned configuration and output profile, Sentiqra returns the same canonical signals.
Version changes are explicit so historical and current analyzer behavior can be distinguished.
Supported languages
Market Intelligence currently supports 8 languages.
| Code | Language | Status |
|---|---|---|
| en | English | Production |
| zh | Chinese | Production |
| ja | Japanese | Production |
| de | German | Production |
| fr | French | Production |
| it | Italian | Production |
| hi | Hindi | Production |
| ko | Korean | 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
Use the result inside your own decision layer
A typical architecture:
News / filing / statement
↓
Sentiqra event classification
↓
Customer market data + issuer mapping + state/history
↓
Research / surveillance / risk model
↓
Customer-defined decision
Sentiqra supplies structured event evidence. Your models, controls, and analysts determine what happens next.
Performance
Built for real-time market-intelligence and surveillance pipelines.
Published latency targets, not measured guarantees - measured snapshot figures are on the performance dashboard. Actual latency depends on network conditions, payload size, and load.
Errors, limits, and rate controls
The Market Intelligence API uses standard HTTP response codes:
| Code | Description |
|---|---|
| 400 | Invalid request |
| 401 | Authentication error |
| 403 | Access unavailable |
| 413 | Input too large |
| 429 | Rate or quota exceeded |
| 500 | Internal error |
| 503 | Temporary unavailability |
For retryable responses, follow documented backoff and Retry-After behavior.
| Header | Description |
|---|---|
| X-RateLimit-Limit | Max requests per second |
| X-RateLimit-Remaining | Remaining requests in current window |
| X-RateLimit-Reset | Unix timestamp when window resets |
Data handling
Sentiqra documents separately what crosses and remains within the service boundary:
Raw request content
Submitted text is processed in memory and not retained. No model training on your data.
Signal metadata
Individual signal results are not stored. Only aggregate counters are derived from them before the response is sent, apart from the bounded idempotency replay copy and webhook delivery payloads described in the retention schedule.
Operational metadata
Request status, key identifiers, latency, and billing information are logged for operational purposes.
Code examples
All examples use environment variables for API keys - do not hard-code keys in source.
curl -X POST https://sentiqra.tech/v1/analyze \
-H "Authorization: Bearer $SENTIQRA_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"text": "The company announced an all-cash acquisition expected to close next quarter.",
"language": "en",
"analyzers": [
"finance"
]
}'
Reading Market Intelligence output
What you can safely infer from a result - and what you must not.
Intended task
Classify market-relevant text - headlines, filings prose, desk notes - into documented event groups like earnings, guidance, M&A, and distress.
Input requirements
text- the only field analyzed; up to 4,096 Unicode code points. Over the limit is rejected withinput_too_long, never truncated.language- must be a language this analyzer supports. Unsupported codes are rejected with400 unsupported_language, never analyzed as a different language.analyzers- include"finance"; 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. - Reads one text at a time - no position data, portfolio context, or market feeds are inputs.
Ordinary positive
“Acme raised full-year revenue guidance after Q3 results beat consensus; the board also authorized a buyback.”
Safe inference: The text describes earnings, guidance, and capital-return events. Route it to the sectors and instruments your coverage maps to.
Confusing negative · Insufficient context
“Traders speculated that Acme might raise guidance when it reports next quarter.”
What happens: Event-group signals can fire on speculation: the text describes a possible guidance event in the documented vocabulary. A signal marks what the text is about - not that the event is confirmed.
Why it's tricky: Rumors, previews, and post-event coverage share vocabulary with confirmed announcements. The Information Quality & Social Signals group exists partly for this distinction, but no signal confirms that a described event actually happened or that figures are accurate.
What you can safely infer
- Which documented event types the text describes, and at what signal-match strength.
- That results are reproducible - the same filing text on the same pinned configuration always classifies the same way.
What you must not infer
- ✕That a described event is confirmed, accurate, or material.
- ✕A price or trading recommendation - signals classify text, they do not predict markets.
- ✕That unflagged text is market-irrelevant - a missing signal is "not detected," never "ignore."
Boundary: Signals describe the language of a text, not market facts. Market Intelligence is not investment advice and does not verify that a reported event occurred.