> ## Documentation Index > Fetch the complete documentation index at: https://docs.tuteliq.ai/llms.txt > Use this file to discover all available pages before exploring further. # Detect grooming patterns in conversations > Analyze a sequence of messages for multi-stage grooming tactics: trust building, isolation, secrecy requests, boundary testing, and sexual escalation. Accepts full conversation history with sender roles to detect patterns that single-message analysis would miss. Returns grooming risk level, identified tactics as flags, and recommended intervention actions. ## OpenAPI ````yaml https://api.tuteliq.ai/docs/json post /api/v1/safety/grooming openapi: 3.1.0 info: title: Tuteliq API description: > # AI-Powered Child Safety API You're building a chat feature for a kids' learning app. A user sends a message that looks innocuous on the surface but contains subtle grooming escalation patterns. Tuteliq catches it, scores the risk by the child's age group, and gives your trust & safety team an actionable report — all in under 400ms. One API call replaces months of in-house ML work. --- ## KOSA Harm Categories Coverage | Harm Category | Endpoint | Status | |--------------|----------|--------| | Eating Disorders | `/safety/unsafe` | ✅ Covered | | Substance Use | `/safety/unsafe` | ✅ Covered | | Suicidal Behaviors | `/safety/unsafe` | ✅ Covered | | Depression & Anxiety | `/safety/unsafe` + `/analysis/emotions` | ✅ Covered | | Compulsive Usage | `/safety/unsafe` | ✅ Covered | | Harassment & Bullying | `/safety/bullying` | ✅ Covered | | Sexual Exploitation | `/safety/grooming` + `/safety/unsafe` | ✅ Covered | | Voice & Audio Threats | `/safety/voice` | ✅ Covered | | Visual Content Risks | `/safety/image` | ✅ Covered | --- ## Key Features - **Age-Calibrated Severity** — Risk scores adjust across four age brackets (under 10, 10–12, 13–15, 16–17) so moderation matches developmental context. - **Nuanced Context Recognition** — Distinguishes hyperbolic teen language from genuine crisis signals, dramatically reducing false positives. - **Grooming Pattern Detection** — Identifies multi-stage grooming tactics: trust escalation, secrecy requests, isolation attempts, and boundary violations. - **Emotional Trend Analysis** — Tracks persistent mood patterns across conversations to surface early indicators of declining mental health. - **Voice & Image Analysis** — Upload audio or images for transcription, OCR, and full safety analysis in a single call. - **Real-time Voice Streaming** — WebSocket endpoint for live audio moderation with configurable flush intervals and per-category alerts. - **Guidance & Reports** — Generate age-appropriate action plans and professional incident reports ready for handoff to human reviewers. - **Batch Processing & Webhooks** — Analyze up to 50 items per batch call, with HMAC-signed webhook alerts for critical incidents. --- ## Credits per Action | Endpoint | Credits | Notes | |----------|---------|-------| | `detectBullying` | 1 | Single text analysis | | `detectUnsafe` | 1 | Single text analysis | | `detectGrooming` | 1 per 10 msgs | `ceil(messages / 10)`, min 1 | | `analyzeEmotions` | 1 per 10 msgs | `ceil(messages / 10)`, min 1 | | `getActionPlan` | 2 | Longer generation | | `generateReport` | 3 | Structured output | | `analyzeVoice` | 5 | Transcription + analysis | | `analyzeImage` | 3 | Vision + OCR + analysis | Every response includes a `credits_used` field. Credit balance is also available via the `X-Credits-Remaining` response header. --- ## Quick Start **1.** Get your API key at [tuteliq.ai/dashboard](https://tuteliq.ai/dashboard) **2.** Install the SDK: ```bash npm install @tuteliq/sdk ``` **3.** Make your first call: ```typescript import Tuteliq from '@tuteliq/sdk' const tuteliq = new Tuteliq({ apiKey: 'YOUR_API_KEY' }) const result = await tuteliq.detectUnsafe({ content: "Don't talk to your parents about us meeting up", context: { age_group: "13-15" } }) console.log(result.unsafe) // true console.log(result.categories) // ["grooming_adjacent", "secrecy"] console.log(result.severity) // "high" console.log(result.recommended_action) // "Escalate to moderator" ``` --- ## Performance | Metric | Value | |--------|-------| | Average latency | ~400ms | | p95 latency | ~800ms | | Uptime SLA | 99.9% | Check real-time status at [tuteliq.ai/status](https://tuteliq.ai/status) version: 1.0.0 contact: name: Tuteliq Support url: https://tuteliq.ai email: support@tuteliq.ai license: name: Proprietary url: https://tuteliq.ai/terms servers: - url: https://api.tuteliq.ai description: Production server - url: http://localhost:3000 description: Development server security: - bearerAuth: [] - apiKeyHeader: [] tags: - name: Safety description: >- Core detection endpoints for all nine KOSA harm categories. Supports text, voice, and image input with age-calibrated severity scoring. - name: Fraud description: >- Financial and social fraud detection — social engineering, app fraud, romance scams, and money mule recruitment. Identifies tactics targeting minors and vulnerable users with evidence-based scoring. - name: Safety Extended description: >- Extended safety detection — gambling harm, coercive control, vulnerability exploitation with cross-endpoint modifiers, and radicalisation. Requires Indie tier or above. - name: Analyse description: >- Multi-endpoint analysis. Fan-out a single text to up to 10 detection endpoints in parallel with aggregated results, vulnerability modifier support, and per-endpoint breakdowns. - name: Analysis description: >- Emotional intelligence endpoints. Analyze conversations for dominant emotions, sentiment trends (improving/stable/worsening), and early indicators of depression or anxiety. Designed to surface mental health risks before they escalate. - name: Guidance description: >- Post-detection action plans tailored by audience. Generate age-appropriate guidance for children, parents, or platform trust & safety teams — complete with reading-level calibration and tone adjustment. Goes beyond "here's a risk score" to answer "what do we do about it?" - name: Reports description: >- Professional incident report generation for schools, counselors, and moderators. Converts raw conversation data into structured reports with risk levels, categorized findings, and recommended next steps — ready for handoff to human reviewers. - name: Batch description: >- Analyze up to 50 items in a single request with optional parallel processing. Supports all analysis types (bullying, grooming, unsafe, emotions). Built for production pipelines that need to process backlogs or moderate content in bulk. - name: Webhooks description: >- Real-time notification endpoints for receiving alerts when critical incidents are detected. Full CRUD management with HMAC-SHA256 signed payloads, automatic retry on failure, secret regeneration, and test delivery — everything you need for production event-driven architectures. - name: Usage description: >- API usage tracking, quota monitoring, and rate limit status. View daily summaries, historical trends, per-tool breakdowns, and monthly billing period usage. Includes upgrade recommendations when approaching limits. - name: Policy description: >- Customize detection behavior for your use case. Configure sensitivity thresholds, category weights, and moderation rules without changing your integration code. - name: Pricing description: >- Public pricing plan information. Browse available tiers, features, and limits. The public endpoint requires no authentication; detailed plan info requires an API key. - name: Account description: >- GDPR-compliant account data management. Exercise the Right to Erasure (Article 17), Right to Data Portability (Article 20), and Right to Rectification (Article 16). Manage consent records and access your full audit trail. Available to all tiers — privacy is not a premium feature. - name: Compliance description: >- Public transparency endpoints for GDPR compliance. Machine-readable Data Processing Agreement (DPA), current sub-processor list, and data retention schedules. No authentication required — anyone can verify our data practices. - name: Admin description: >- Administrative endpoints for breach management and data retention. Log, track, and manage data breach incidents with full audit trails and notification status tracking. Trigger manual data retention cleanup when needed. - name: Health description: >- Health check and monitoring endpoints. Liveness and readiness probes for Kubernetes/Cloud Run, full dependency health checks, and detailed component status for debugging. - name: Status description: >- Public API status and uptime monitoring. Component-level health (API, database, cache, AI engine), uptime percentages, and an embeddable status page. Use /status/ping for external monitoring services like UptimeRobot. externalDocs: description: KOSA Compliance Documentation url: https://tuteliq.ai/docs/kosa-compliance paths: /api/v1/safety/grooming: post: tags: - Safety summary: Detect grooming patterns in conversations description: >- Analyze a sequence of messages for multi-stage grooming tactics: trust building, isolation, secrecy requests, boundary testing, and sexual escalation. Accepts full conversation history with sender roles to detect patterns that single-message analysis would miss. Returns grooming risk level, identified tactics as flags, and recommended intervention actions. requestBody: content: application/json: schema: type: object required: - messages properties: messages: type: array maxItems: 100 items: type: object required: - sender_role - text properties: sender_role: type: string description: Role of sender (e.g., "adult", "child") text: type: string maxLength: 10000 description: Message text sender_age: type: number description: >- Optional numeric age of THIS message's sender. Strengthens age-gap analysis without forcing the model to infer it from the role label. description: >- Sequence of messages to analyze. Consecutive same-role messages of ≤3 characters are automatically defragmented before tactic analysis to prevent letter-by-letter evasion. continuation_token: type: string description: >- Opaque signed token from a previous /grooming call. Carries derived analysis state across calls without server-side storage. reset_conversation: type: boolean description: >- Discard any continuation_token and start a fresh conversation. message_id: type: string maxLength: 128 description: >- Optional customer-side identifier for this batch (used as the evidence pointer in the issued continuation_token). context: type: object properties: child_age: type: number description: Age of the child / minor in the conversation. participant_age: type: number description: >- Optional age of the non-minor participant. When known (e.g. on age-verified platforms), this lets the model compute the actual age gap rather than infer it. platform: type: string description: Platform name language: type: string description: Language code (e.g., "en") options: type: object properties: support_threshold: type: string enum: - low - medium - high - critical description: >- Minimum severity to show crisis support resources (default: high). Critical always shows. verdict_only: type: boolean default: false description: >- Fast mode: omit the per-message `message_analysis` array from the response, reducing output length and latency. All other fields are unchanged. support_threshold: type: string enum: - low - medium - high - critical description: >- Top-level alias for options.support_threshold. Minimum severity to show crisis support resources (default: high). Critical always shows. external_id: type: string maxLength: 255 description: >- Your unique identifier (e.g. message ID, content ID) for correlating Tuteliq results with your own system. Echoed back in the response and included in webhook payloads so you can match alerts to the original content. customer_id: type: string maxLength: 255 description: >- Your end-customer identifier for multi-tenant / B2B2C scenarios. If you serve multiple customers (schools, apps, brands) from a single API key, set this to route webhook alerts to the correct customer. Echoed back in the response and included in webhook payloads as "customerId". metadata: type: object additionalProperties: true maxProperties: 20 description: >- Arbitrary key-value pairs for additional context (e.g. { "channel": "discord", "region": "eu" }). Stored with the detection result, echoed in the response, and included in webhook payloads. Maximum 20 properties. incident_moderation_enabled: type: boolean description: >- Per-call override of your account incident logging setting. When set, it takes precedence over the account-level flag for THIS request: true forces the incident to be persisted, false suppresses persistence. Omit to use your account default (which itself defaults to enabled). Lets you control incident logging per request, e.g. suppress logging for test traffic. required: true responses: '200': description: Default Response content: application/json: schema: type: object properties: grooming_risk: type: string enum: - none - low - medium - high - critical description: >- Grooming-risk level. "low" indicates a signal worth monitoring but no action required; branch your alerting on `recommended_action` (`flag_for_review` / `block` / `immediate_intervention`), not the bare presence of a low-level risk. confidence: type: number flags: type: array items: type: string rationale: type: string risk_score: type: number recommended_action: type: string enum: - none - monitor - flag_for_review - block - immediate_intervention description: >- Routing key — a single stable token, safe to switch on. Ordered weakest to strongest: `none` (no signal), `monitor` (log, no human needed), `flag_for_review` (queue for a moderator), `block` (withhold or limit the content), `immediate_intervention` (crisis path). Human-readable guidance is in `action_detail`, not here. action_detail: type: string description: >- Optional one-to-two-sentence explanation of `recommended_action`, intended for a moderator UI. Never branch on this field — it is free text and its wording is not stable across releases. message_analysis: type: array description: >- Per-message risk breakdown showing how risk escalates across the conversation items: type: object properties: message_index: type: number description: 1-based index of the message risk_score: type: number description: Individual risk score (0.0-1.0) flags: type: array items: type: string description: Tactics detected in this message summary: type: string description: Brief explanation of risk contribution language: type: string description: >- Language code used for analysis (auto-detected or provided) language_status: type: string enum: - stable - beta description: >- Language support maturity: "stable" (en) or "beta" (all others) credits_used: type: number description: Number of credits consumed by this request continuation_token: type: string description: >- Privacy-first signed token carrying derived analysis state across calls. Pass back on the next /grooming request. continuation_expires_at: type: string description: ISO 8601 expiry timestamp of the continuation_token. state_source: type: string enum: - token - fresh - reset description: How prior state was sourced for this call. analysis_status: type: string enum: - ok - engine_error - out_of_scope_adults description: >- Status of the analysis. `ok` is the default. `engine_error` means the analysis engine could not produce a verdict (malformed/adversarial input) and `recommended_action` is forced to `flag_for_review`. `out_of_scope_adults` means the caller provided 2+ adult ages (via `context.participant_age`, `context.child_age`, or per-message `sender_age`) and the call was short-circuited as out of scope for grooming — consider /safety/coercive-control or /safety/social-engineering for adult-adult dynamics. external_id: type: string description: Echo of the external_id you provided in the request customer_id: type: string description: Echo of the customer_id you provided in the request metadata: type: object additionalProperties: true description: Echo of the metadata you provided in the request support: type: object description: >- Country-specific crisis helplines and response guidance (only included for high/critical severity) properties: country: type: string country_name: type: string emergency_number: type: string helplines: type: array items: type: object properties: name: type: string number: type: string description: type: string category: type: string available: type: string response_guide: type: object properties: category: type: string immediateActions: type: array items: type: string resources: type: array items: type: object properties: name: type: string description: type: string url: type: string components: securitySchemes: bearerAuth: type: http scheme: bearer description: API key as Bearer token apiKeyHeader: type: apiKey in: header name: x-api-key description: API key in header ````