# Tuteliq

> Documentation for the Tuteliq API — AI-powered child safety detection and synthetic content analysis for text, voice, images, and video.

- [Introduction](https://docs.tuteliq.ai/index.md): Detect grooming, bullying, self-harm, fraud, and more with a single API call
- [Quickstart](https://docs.tuteliq.ai/quickstart.md): Get up and running with Tuteliq in under 5 minutes
- [Authentication](https://docs.tuteliq.ai/authentication.md): How to authenticate with the Tuteliq API
- [How It Works](https://docs.tuteliq.ai/how-it-works.md): Understand Tuteliq's detection pipeline — from raw content to actionable safety scores
- [How Tuteliq compares](https://docs.tuteliq.ai/comparison.md): How Tuteliq differs from keyword filters and general-purpose moderation APIs for detecting grooming, bullying, gaming toxicity, fraud, and coded language. When to choose a context-aware safety API.
- [Benchmarks and accuracy](https://docs.tuteliq.ai/benchmarks.md): How Tuteliq measures coded-language and filter-evasion detection, what the methodology covers, and multilingual coverage.
- [Gaming and social chat moderation](https://docs.tuteliq.ai/gaming-chat-moderation.md): Real-time content moderation API for gaming and social platforms. Detect toxicity, harassment, coded slang, grooming, and coordinated abuse in game and social chat, with context that tells trash-talk apart from genuine harm.
- [AI Agent Integration](https://docs.tuteliq.ai/ai-agents.md): Machine-readable documentation for AI agents and LLM-powered applications
- [Pricing & Credits](https://docs.tuteliq.ai/credits.md): Understand the Tuteliq credit system, pricing tiers, and per-endpoint costs
- [Changelog](https://docs.tuteliq.ai/changelog.md): Latest updates to the Tuteliq API
- [Node.js SDK](https://docs.tuteliq.ai/sdks/node.md): Install and use the Tuteliq Node.js SDK
- [Python SDK](https://docs.tuteliq.ai/sdks/python.md): Install and use the Tuteliq Python SDK
- [Swift SDK](https://docs.tuteliq.ai/sdks/swift.md): Install and use the Tuteliq Swift SDK
- [Kotlin SDK](https://docs.tuteliq.ai/sdks/kotlin.md): Install and use the Tuteliq Kotlin SDK
- [Flutter SDK](https://docs.tuteliq.ai/sdks/flutter.md): Install and use the Tuteliq Flutter SDK
- [React Native SDK](https://docs.tuteliq.ai/sdks/react-native.md): Install and use the Tuteliq React Native SDK
- [.NET SDK](https://docs.tuteliq.ai/sdks/dotnet.md): Install and use the Tuteliq .NET SDK
- [Unity SDK](https://docs.tuteliq.ai/sdks/unity.md): Install and use the Tuteliq Unity SDK
- [CLI](https://docs.tuteliq.ai/sdks/cli.md): Install and use the Tuteliq command-line interface
- [MCP Server for Content Moderation and Child Safety](https://docs.tuteliq.ai/mcp-server.md): Connect Claude, Cursor or any MCP client to Tuteliq over OAuth. Around 80 tools for grooming detection, content moderation, incident review and compliance, with no API key to configure.
- [MCP Authentication and Token Lifetime](https://docs.tuteliq.ai/mcp-server/authentication.md): OAuth 2.1 with dynamic client registration and PKCE for the Tuteliq MCP server, plus token lifetime, refresh rotation, static tokens for headless use, and stdio.
- [Moderation Workflows with an AI Agent](https://docs.tuteliq.ai/mcp-server/moderation.md): Work a Tuteliq moderation queue with an AI agent over MCP. Triage by severity, inspect incidents, record decisions with a signed audit trail, and understand what an agent is allowed to decide.
- [MCP Tool Reference](https://docs.tuteliq.ai/mcp-server/tools.md): Every tool exposed by the Tuteliq MCP server, grouped by purpose, plus the full list of tools that change or delete data.
- [Vercel AI SDK](https://docs.tuteliq.ai/integrations/vercel-ai-sdk.md): Wrap a Vercel AI SDK chatbot with inbound and outbound Tuteliq moderation using language model middleware.
- [Roblox Integration](https://docs.tuteliq.ai/integrations/roblox.md): Add real-time child safety moderation to your Roblox experience
- [Discord Integration](https://docs.tuteliq.ai/integrations/discord.md): AI-powered child safety monitoring for Discord servers
- [Slack Integration](https://docs.tuteliq.ai/integrations/slack.md): AI-powered child safety monitoring for Slack workspaces
- [Telegram Integration](https://docs.tuteliq.ai/integrations/telegram.md): AI-powered child safety monitoring for Telegram groups
- [Age & Identity Verification](https://docs.tuteliq.ai/verification.md): Production-grade age and identity verification with document intelligence, biometric matching, liveness detection, and multi-layer fraud prevention — covering 45 countries
- [Cross-device verification flow](https://docs.tuteliq.ai/verification/cross-device-flow.md): End-to-end integration guide for embedding Tuteliq verification in your app via a webview, mobile redirect, or QR-code handoff. Covers session creation, live status updates, webview hosting, and result retrieval.
- [Document Checks](https://docs.tuteliq.ai/verification/document-checks.md): 45-country document number validation, ICAO 9303 MRZ parsing, and PDF417 barcode decoding
- [Liveness Detection](https://docs.tuteliq.ai/verification/liveness-detection.md): Multi-signal visual liveness analysis prevents photo, screen, printout, and deepfake spoofing attacks
- [Fraud Prevention](https://docs.tuteliq.ai/verification/fraud-prevention.md): 7 cross-referencing layers, deterministic document validation, MRZ check-digit verification, and geographic consistency checks
- [Composable safety primitives](https://docs.tuteliq.ai/composability.md): How Tuteliq detectors enrich each other through cross_endpoint_modifier and vulnerability_profile.
- [Policy automation](https://docs.tuteliq.ai/policy-automation.md): Encode your own escalation thresholds and automated actions as server-side rules, evaluated on every detection.
- [Grooming detection](https://docs.tuteliq.ai/grooming-detection.md): How Tuteliq detects child grooming patterns as a sequence of tactics, not a single signal.
- [Bullying and toxicity detection](https://docs.tuteliq.ai/bullying-toxicity-detection.md): Detect cyberbullying, harassment, and gaming toxicity in chat, including coded slang, emoji, and deliberate filter evasion, with context that tells trash-talk apart from genuine harm.
- [Fast mode (verdict-only)](https://docs.tuteliq.ai/fast-mode.md): Real-time content moderation with Tuteliq's verdict-only fast mode. Screen live chat with low latency by returning the conversation verdict without the per-message breakdown.
- [Language Support](https://docs.tuteliq.ai/languages.md): Automatic language detection and culture-aware safety analysis in 32 languages: English stable, 31 beta
- [Continuation Tokens](https://docs.tuteliq.ai/continuation-tokens.md): Privacy-first conversation memory. Get conversation-aware detection across many calls without Tuteliq ever storing your conversation.
- [Prescreen Lexicon](https://docs.tuteliq.ai/prescreen-lexicon.md): Tuteliq's SDK-side pattern matcher. Skip the API call for clearly-benign content; attach high-precision signals to the requests you do make. All matching happens on your device.
- [Synthetic Content Detection](https://docs.tuteliq.ai/synthetic-content.md): Multi-signal forensic detection of AI-generated text, images, audio, and video — deepfakes, voice cloning, synthetic identities, and AI-enhanced child exploitation content
- [Voice & Video Streaming](https://docs.tuteliq.ai/voice-streaming.md): Real-time voice and video moderation via WebSocket
- [Video Analysis](https://docs.tuteliq.ai/video-analysis.md): Analyze uploaded videos for visual safety concerns across extracted frames
- [Document Analysis](https://docs.tuteliq.ai/document-analysis.md): Upload PDFs for multi-endpoint safety analysis with per-page detection, chain-of-custody hashing, and zero-retention processing
- [Webhooks](https://docs.tuteliq.ai/webhooks.md): Receive real-time alerts for critical safety incidents
- [Error Handling](https://docs.tuteliq.ai/error-handling.md): Handle Tuteliq API errors gracefully
- [KOSA Coverage](https://docs.tuteliq.ai/kosa-compliance.md): How Tuteliq covers all nine Kids Online Safety Act harm categories
- [EU KIDS Act Coverage](https://docs.tuteliq.ai/eu-kids-act.md): What the proposed EU KIDS Act asks of platforms, and which Tuteliq capabilities address the age-assurance and minor-protection halves of it
- [GDPR Compliance](https://docs.tuteliq.ai/gdpr.md): Data privacy endpoints for GDPR compliance
- [Incident Logging Control](https://docs.tuteliq.ai/incident-logging.md): Turn off incident storage so Tuteliq keeps no record of your detections, and set how long incidents are retained
- [Caching & content storage](https://docs.tuteliq.ai/caching.md): What Tuteliq caches, what it never stores, and how to opt out for fresh evaluations.
- [Trust Center](https://docs.tuteliq.ai/trust.md): Security, compliance, and transparency at Tuteliq
- [Free Certification](https://docs.tuteliq.ai/certification.md): Earn your official Tuteliq child safety certificate — free, verified, and shareable
- [Secure Development Lifecycle](https://docs.tuteliq.ai/sdlc.md): How Tuteliq develops, reviews, tests, and deploys code to production
- [Security Policy](https://docs.tuteliq.ai/security.md): How to report a vulnerability to Tuteliq, what we commit to in return, and the rules for testing a child-safety API
- [Vendor Reference Disclosure](https://docs.tuteliq.ai/vendor-reference-disclosure.md): Tuteliq's completed disclosure against TUT-CSDT-001, the transparency framework we wrote, including where we fall short
- [Boundary Pushing Re-Adjudication](https://docs.tuteliq.ai/boundary-pushing-readjudication.md): Per-item reasoning for the sixteen TUT-100 turns relabelled away from boundary_pushing, published so the adjudication can be checked rather than trusted
- [API Reference](https://docs.tuteliq.ai/api-reference/introduction.md): Complete reference for all Tuteliq API endpoints — authentication, rate limits, error handling, and endpoint groups
- [Detect bullying, harassment, and intimidation in text](https://docs.tuteliq.ai/api-reference/safety/detect-bullying-harassment-and-intimidation-in-text.md): Analyze a message for bullying indicators including verbal abuse, social exclusion, threats, and cyberbullying patterns. Returns severity (low/medium/high/critical), bullying type classification, confidence score, and a recommended action. Risk scores are age-calibrated when context.ageGroup is prov…
- [Analyze a PDF or image for safety and compliance concerns](https://docs.tuteliq.ai/api-reference/safety/analyze-a-pdf-or-image-for-safety-and-compliance-concerns.md): Upload a PDF (max 50MB, max 100 pages) or a single image (png, jpeg, webp) for multi-endpoint safety analysis. PDFs are read from the text layer per page; images are read by OCR and analysed as a one-page document. Choose which detectors run with the endpoints field. For a messaging screenshot, set…
- [Detect grooming patterns in conversations](https://docs.tuteliq.ai/api-reference/safety/detect-grooming-patterns-in-conversations.md): 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, identifi…
- [Analyze image for visual and textual safety concerns](https://docs.tuteliq.ai/api-reference/safety/analyze-image-for-visual-and-textual-safety-concerns.md): Upload an image (png, jpg, gif, webp — max 10MB) for dual-layer analysis: Vision AI classifies visual content (nudity, violence, weapons, drugs, self-harm imagery) while OCR extracts embedded text for separate safety analysis. Returns visual categories, extracted text, face detection, and combined o…
- [Detect AI-generated or synthetic content](https://docs.tuteliq.ai/api-reference/safety/detect-ai-generated-or-synthetic-content.md): Analyzes text for AI-generated content indicators including LLM-generated text, synthetic identities, AI-enhanced grooming scripts, and synthetic CSAM. Classifies content as confirmed_synthetic, suspected_synthetic, unknown, or confirmed_authentic.
- [Detect AI-generated or cloned voice audio](https://docs.tuteliq.ai/api-reference/safety/detect-ai-generated-or-cloned-voice-audio.md): Multi-signal audio analysis: transcription-based text analysis plus spectral analysis (mel spectrogram semantic analysis, audio statistics for TTS indicators). Classifies as confirmed_synthetic, suspected_synthetic, unknown, or confirmed_authentic.
- [Detect AI-generated or synthetic images](https://docs.tuteliq.ai/api-reference/safety/detect-ai-generated-or-synthetic-images.md): Multi-signal forensic analysis: semantic analysis, EXIF metadata, pixel statistics, C2PA Content Credentials, watermark detection, and perceptual hashing. Classifies as confirmed_synthetic, suspected_synthetic, unknown, or confirmed_authentic.
- [Detect deepfake or AI-generated video](https://docs.tuteliq.ai/api-reference/safety/detect-deepfake-or-ai-generated-video.md): Multi-signal forensic video analysis: per-frame semantic analysis, temporal face consistency, lip-sync correlation, audio spectral analysis, and transcription. Classifies as confirmed_synthetic, suspected_synthetic, unknown, or confirmed_authentic.
- [Detect KOSA-aligned harm signals in text](https://docs.tuteliq.ai/api-reference/safety/detect-kosa-aligned-harm-signals-in-text.md): Comprehensive safety analysis covering all KOSA harm categories: self-harm and suicidal ideation, eating disorders, substance use, depression/anxiety indicators, compulsive usage patterns, sexual content, violence, and hate speech. Returns categorized findings with age-calibrated severity scoring. T…
- [Analyze video for visual safety concerns across extracted frames](https://docs.tuteliq.ai/api-reference/safety/analyze-video-for-visual-safety-concerns-across-extracted-frames.md): Upload a video file (mp4, webm, quicktime, avi — max 100MB, max 10 min). Extracts key frames at even intervals and runs vision analysis on each frame. Returns per-frame results, flagged timestamps, and an aggregated overall risk score. Ideal for moderating uploaded video content, screen recordings,…
- [Analyze voice/audio for safety concerns with transcription](https://docs.tuteliq.ai/api-reference/safety/analyze-voiceaudio-for-safety-concerns-with-transcription.md): Upload an audio file (mp3, wav, m4a, ogg, flac, webm, mp4 — max 25MB) for automatic transcription followed by full safety analysis on the transcript. Returns timestamped segments, per-category analysis (bullying, grooming, unsafe, emotions), and an overall risk score. Ideal for monitoring voice chat…
- [Detect app fraud and financial scam patterns](https://docs.tuteliq.ai/api-reference/fraud/detect-app-fraud-and-financial-scam-patterns.md): Analyzes text content for app fraud indicators including payment coercion, account takeover, safe account scams, invoice fraud, impersonation, investment pressure, and emotional financial exploitation.
- [Detect money mule recruitment attempts](https://docs.tuteliq.ai/api-reference/fraud/detect-money-mule-recruitment-attempts.md): Analyzes text content for money mule recruitment indicators including easy money promises, account access requests, multi-level recruitment, risk minimisation, secrecy demands, social pressure, and coercion.
- [Detect romance scam indicators in conversation](https://docs.tuteliq.ai/api-reference/fraud/detect-romance-scam-indicators-in-conversation.md): Analyzes text and conversation history for romance scam patterns including love bombing, isolation, fabricated crises, investment lures, identity deception, financial grooming, guilt manipulation, and crypto redirect tactics.
- [Detect social engineering tactics in text](https://docs.tuteliq.ai/api-reference/fraud/detect-social-engineering-tactics-in-text.md): Analyzes text content for social engineering manipulation tactics including authority impersonation, urgency fabrication, pretexting, information elicitation, trust exploitation, fear induction, and quid pro quo patterns.
- [Detect coercive control patterns](https://docs.tuteliq.ai/api-reference/safety-extended/detect-coercive-control-patterns.md): Analyzes text and conversation history for coercive control patterns including monitoring, isolation, financial control, threats, degradation, micromanagement, gaslighting, and child weaponisation.
- [Detect linguistic distress-signal patterns (pre-vulnerability indicators)](https://docs.tuteliq.ai/api-reference/safety-extended/detect-linguistic-distress-signal-patterns-pre-vulnerability-indicators.md): Analyses text for the presence of linguistic patterns historically associated with distress (loneliness expressions, isolation language, hopelessness phrases, trust-seeking openers, withdrawal references, family-conflict mentions). Returns pattern detections and, where applicable, downstream exploit…
- [Detect gambling harm indicators](https://docs.tuteliq.ai/api-reference/safety-extended/detect-gambling-harm-indicators.md): Analyzes text content for gambling harm indicators including chasing losses, desperation, borrowing, loss of control, relationship impact, financial harm, and denial patterns.
- [Detect radicalisation and extremism indicators](https://docs.tuteliq.ai/api-reference/safety-extended/detect-radicalisation-and-extremism-indicators.md): Analyzes text and conversation history for radicalisation indicators including ideological seeding, identity exploitation, in-group bonding, out-group dehumanisation, grievance amplification, violence normalisation, operational planning, and isolation from moderating influences.
- [Detect tech-facilitated gender-based violence](https://docs.tuteliq.ai/api-reference/safety-extended/detect-tech-facilitated-gender-based-violence.md): Analyzes text for tech-facilitated gender-based violence (TFGBV) patterns including image-based abuse, cyber stalking, online harassment, doxing, impersonation, outing, post-separation abuse, sextortion, digital coercion, sexualised deepfakes, and gendered hate speech. Returns TFGBV amplifier assess…
- [Detect exploitation of vulnerable individuals](https://docs.tuteliq.ai/api-reference/safety-extended/detect-exploitation-of-vulnerable-individuals.md): Analyzes text for vulnerability exploitation including age targeting, emotional exploitation, cognitive exploitation, situational vulnerability, trust abuse, and information asymmetry. Returns additional cross-endpoint modifier and vulnerability profile.
- [Fan-out analysis across multiple detection endpoints](https://docs.tuteliq.ai/api-reference/analyse/fan-out-analysis-across-multiple-detection-endpoints.md): Submit text to multiple detection endpoints in a single request. All endpoints run in parallel via Promise.allSettled. If vulnerability-exploitation is included and succeeds, its cross_endpoint_modifier is applied to all other results' severity scores (clamped to 1.0). Maximum 10 endpoints per reque…
- [Fan-out analysis across multiple detection endpoints](https://docs.tuteliq.ai/api-reference/analyse/fan-out-analysis-across-multiple-detection-endpoints.md): Submit text to multiple detection endpoints in a single request. All endpoints run in parallel via Promise.allSettled. If vulnerability-exploitation is included and succeeds, its cross_endpoint_modifier is applied to all other results' severity scores (clamped to 1.0). Maximum 10 endpoints per reque…
- [Analyze emotional patterns and mental health indicators in conversation](https://docs.tuteliq.ai/api-reference/analysis/analyze-emotional-patterns-and-mental-health-indicators-in-conversation.md): Analyze a conversation for dominant emotions, sentiment trajectory (improving/stable/worsening), and early mental health risk indicators. Surfaces persistent patterns of sadness, anxiety, anger, or withdrawal that may indicate depression or declining wellbeing. Returns emotion scores, trend analysis…
- [Generate age-appropriate action plan for a safety situation](https://docs.tuteliq.ai/api-reference/guidance/generate-age-appropriate-action-plan-for-a-safety-situation.md): Generate a step-by-step action plan tailored to the audience: child-friendly guidance (with reading-level calibration), parent advice, or platform trust & safety team procedures. Adjusts tone, vocabulary, and recommended steps based on the child's age and incident severity. Goes beyond detection to…
- [Generate professional incident report from conversation data](https://docs.tuteliq.ai/api-reference/reports/generate-professional-incident-report-from-conversation-data.md): Convert raw conversation messages into a structured incident report suitable for school counselors, moderators, or trust & safety teams. Returns a narrative summary, overall risk level, categorized findings, and recommended next steps. Accepts optional metadata (conversation ID, child age, timestamp…
- [Analyze up to 50 items in a single request](https://docs.tuteliq.ai/api-reference/batch/analyze-up-to-50-items-in-a-single-request.md): Submit multiple analysis tasks in one API call with optional parallel processing. Each item specifies its type (bullying, grooming, unsafe, or emotions) and data. Returns individual results for each item plus a summary with total/successful/failed counts and processing time. Ideal for content modera…
- [Delete a webhook](https://docs.tuteliq.ai/api-reference/webhooks/delete-a-webhook.md): Permanently delete a webhook
- [List all webhooks](https://docs.tuteliq.ai/api-reference/webhooks/list-all-webhooks.md): Returns all webhooks configured for the authenticated user
- [Create a webhook](https://docs.tuteliq.ai/api-reference/webhooks/create-a-webhook.md): Create a new webhook endpoint for receiving notifications
- [Test a webhook](https://docs.tuteliq.ai/api-reference/webhooks/test-a-webhook.md): Send a test payload to verify webhook configuration
- [Regenerate webhook secret](https://docs.tuteliq.ai/api-reference/webhooks/regenerate-webhook-secret.md): Generate a new signing secret for the webhook
- [Update a webhook](https://docs.tuteliq.ai/api-reference/webhooks/update-a-webhook.md): Update an existing webhook configuration
- [Get usage breakdown by tool and endpoint](https://docs.tuteliq.ai/api-reference/usage/get-usage-breakdown-by-tool-and-endpoint.md): Returns request counts broken down by analysis tool (bullying, grooming, unsafe, etc.) and endpoint path. Helps identify which safety features your integration uses most for capacity planning and cost optimization.
- [Get usage history over time](https://docs.tuteliq.ai/api-reference/usage/get-usage-history-over-time.md): Returns daily request counts (total, successful, failed) for the past N days (1–30, default 7). Use for trend analysis, usage charts, and identifying peak traffic periods.
- [Get monthly billing period usage and upgrade recommendations](https://docs.tuteliq.ai/api-reference/usage/get-monthly-billing-period-usage-and-upgrade-recommendations.md): Returns your current billing period usage (calls used vs. limit), tier details, rate limits, and days remaining. Includes smart upgrade recommendations when you approach 80% usage or have fewer than 200 calls remaining. Links to dashboard, pricing, and credit purchase pages.
- [Get real-time rate limit and quota status](https://docs.tuteliq.ai/api-reference/usage/get-real-time-rate-limit-and-quota-status.md): Returns your current rate limit status (requests this minute vs. limit) and daily quota (requests today vs. limit). Shows remaining capacity for both windows. Use before making bulk requests to avoid hitting limits.
- [Get daily usage summary with quota status](https://docs.tuteliq.ai/api-reference/usage/get-daily-usage-summary-with-quota-status.md): Returns total, successful, and failed request counts for a specific date (defaults to today), along with your tier quota limits and remaining capacity. Use for dashboards and usage monitoring.
- [Get current detection policy configuration](https://docs.tuteliq.ai/api-reference/policy/get-current-detection-policy-configuration.md): Retrieve your active policy configuration including sensitivity thresholds, enabled categories, and custom moderation rules. Policies control how the safety endpoints evaluate and score content for your specific use case.
- [Update detection policy configuration](https://docs.tuteliq.ai/api-reference/policy/update-detection-policy-configuration.md): Apply new policy settings to customize detection behavior. Changes take effect immediately for all subsequent API calls. Use to adjust sensitivity thresholds, enable/disable specific harm categories, or set custom moderation rules for your platform.
- [Get pricing plans](https://docs.tuteliq.ai/api-reference/pricing/get-pricing-plans.md): Returns all active pricing plans. This endpoint is public and does not require authentication.
- [Get detailed pricing plans](https://docs.tuteliq.ai/api-reference/pricing/get-detailed-pricing-plans.md): Returns detailed pricing plan information including limits and endpoints.
- [Withdraw consent for a processing purpose](https://docs.tuteliq.ai/api-reference/account/withdraw-consent-for-a-processing-purpose.md): Withdraw previously given consent for a specific processing type. The withdrawal is recorded with timestamp for audit purposes. Any processing that relied on this consent will cease.
- [Exercise Right to Erasure (GDPR Article 17)](https://docs.tuteliq.ai/api-reference/account/exercise-right-to-erasure-gdpr-article-17.md): Permanently delete all stored account and analysis data associated with your API key. This is irreversible. All detection results, incidents, emotion records, and usage data will be purged. Returns confirmation and count of deleted records.
- [Revoke the customer-registered public key](https://docs.tuteliq.ai/api-reference/account/revoke-the-customer-registered-public-key.md): After revocation, new incidents fall back to server-side encryption (Tuteliq holds the key). Existing incidents stay encrypted under the previous key and remain readable only with its private key. Common reason to revoke: key compromise (then immediately register a new one).
- [Revoke an MCP session token](https://docs.tuteliq.ai/api-reference/account/revoke-an-mcp-session-token.md): Revoke a specific MCP token. The MCP client using this token will be disconnected.
- [Get API key count quota for current tier](https://docs.tuteliq.ai/api-reference/account/get-api-key-count-quota-for-current-tier.md): Return the number of currently active API keys for the authenticated account, the per-tier maximum, and whether another key can be created. Dashboards must call this before minting a new key to enforce the plan limit.
- [View your account audit trail](https://docs.tuteliq.ai/api-reference/account/view-your-account-audit-trail.md): Retrieve a chronological log of all data actions performed on your account: deletions, exports, consent changes, and rectifications. Supports filtering by action type and result limiting. Essential for demonstrating GDPR compliance.
- [Get current consent status](https://docs.tuteliq.ai/api-reference/account/get-current-consent-status.md): Retrieve all active consent records for your account. Optionally filter by consent type. Returns consent type, version accepted, and timestamp for each record.
- [Get the customer-registered public key for end-to-end incident encryption](https://docs.tuteliq.ai/api-reference/account/get-the-customer-registered-public-key-for-end-to-end-incident-encryption.md): Returns the public key currently used to encrypt incident records, or 404 if none is registered. When no key is registered, incidents fall back to server-side encryption (Tuteliq holds the key). Register a public key with POST to switch to true end-to-end encryption — only your dashboard can decrypt…
- [Export all account data (GDPR Article 20)](https://docs.tuteliq.ai/api-reference/account/export-all-account-data-gdpr-article-20.md): Download a complete JSON export of all data associated with your account: detection results, incidents, emotion analyses, consent records, and usage history. Returned as a downloadable JSON file for data portability.
- [List MCP session tokens](https://docs.tuteliq.ai/api-reference/account/list-mcp-session-tokens.md): List all MCP tokens associated with your account. These are scoped tokens issued to MCP clients like Claude Desktop.
- [Rectify account data (GDPR Article 16)](https://docs.tuteliq.ai/api-reference/account/rectify-account-data-gdpr-article-16.md): Correct inaccurate personal data stored in your account. Specify the collection, document ID, and fields to update. Changes are audit-logged with the original and new values for compliance.
- [Rename an MCP session token](https://docs.tuteliq.ai/api-reference/account/rename-an-mcp-session-token.md): Update the display name of an MCP token.
- [Record user consent](https://docs.tuteliq.ai/api-reference/account/record-user-consent.md): Record explicit consent for a specific processing purpose (e.g., data processing, marketing). Stores consent with timestamp, IP address, and user agent for audit compliance. Required before certain data processing activities under GDPR.
- [Register (or rotate) the public key Tuteliq uses to encrypt your incident records](https://docs.tuteliq.ai/api-reference/account/register-or-rotate-the-public-key-tuteliq-uses-to-encrypt-your-incident-records.md): Registers an RSA public key. After registration, all NEW incident records (rationale, visual_description, etc.) are encrypted with a per-record AES key, which is itself wrapped with this RSA key (hybrid scheme RSA-OAEP + AES-256-GCM). Tuteliq cannot decrypt — only your dashboard (with the matching p…
- [Get Data Processing Agreement summary](https://docs.tuteliq.ai/api-reference/compliance/get-data-processing-agreement-summary.md): Returns a machine-readable summary of the Tuteliq Data Processing Agreement (DPA) including data controller/processor roles, processing purposes, sub-processors, security measures, retention policies, and data subject rights. No authentication required — transparency by design.
- [Get data retention schedule](https://docs.tuteliq.ai/api-reference/compliance/get-data-retention-schedule.md): Returns the data retention policy detailing how long each category of data is stored and when it is automatically purged. Covers detection results, audit logs, usage metrics, and account data. No authentication required.
- [List current sub-processors](https://docs.tuteliq.ai/api-reference/compliance/list-current-sub-processors.md): Returns the current list of third-party sub-processors used by Tuteliq, including their purpose and data processing location. Required for GDPR Article 28 transparency. No authentication required.
- [Delete known-synthetic perceptual hashes](https://docs.tuteliq.ai/api-reference/admin/delete-known-synthetic-perceptual-hashes.md)
- [List all recorded breach incidents](https://docs.tuteliq.ai/api-reference/admin/list-all-recorded-breach-incidents.md): Retrieve breach records with optional filtering by status (open, investigating, resolved, closed). Returns breach details, severity, affected user count, and current notification status. Use for breach dashboard and compliance reporting.
- [Get breach incident details](https://docs.tuteliq.ai/api-reference/admin/get-breach-incident-details.md): Retrieve full details of a specific breach incident including timeline, affected users, data categories, notification status, and any notes added during investigation.
- [Cloud IDS threat statistics](https://docs.tuteliq.ai/api-reference/admin/cloud-ids-threat-statistics.md): Returns summary counts of IDS threats by severity and time range.
- [List Cloud IDS threats](https://docs.tuteliq.ai/api-reference/admin/list-cloud-ids-threats.md): Retrieve stored IDS threat events with optional filtering by severity, date range, and limit.
- [Get Cloud IDS threat details](https://docs.tuteliq.ai/api-reference/admin/get-cloud-ids-threat-details.md): Retrieve full details of a specific IDS threat event including raw log data.
- [Update breach status and notification progress](https://docs.tuteliq.ai/api-reference/admin/update-breach-status-and-notification-progress.md): Update a breach incident's status (investigating, resolved, closed) and notification progress. Add notes to document investigation findings or remediation steps. All updates are timestamped for the breach audit trail.
- [Log a new data breach incident](https://docs.tuteliq.ai/api-reference/admin/log-a-new-data-breach-incident.md): Record a data breach for GDPR Article 33/34 compliance. Captures breach details, severity, affected users, and data categories involved. Automatically timestamps the report and initializes notification tracking. Use this as the first step in your breach response workflow.
- [Cloud IDS Pub/Sub push endpoint](https://docs.tuteliq.ai/api-reference/admin/cloud-ids-pubsub-push-endpoint.md): Receives threat notifications from Google Cloud IDS via Pub/Sub push subscription. Verifies the token query parameter before processing.
- [Trigger manual data retention cleanup](https://docs.tuteliq.ai/api-reference/admin/trigger-manual-data-retention-cleanup.md): Manually run the data retention cleanup process to purge records that have exceeded their retention period. Normally runs on a schedule, but can be triggered on-demand for compliance audits or storage management. Returns a summary of deleted records by category.
- [Health check](https://docs.tuteliq.ai/api-reference/health/health-check.md): Returns detailed health status of all dependencies
- [Dependency status (admin)](https://docs.tuteliq.ai/api-reference/health/dependency-status-admin.md): Returns detailed status of each dependency with configuration info. Requires admin authentication via X-Admin-Secret header or Authorization: Bearer token. Other health endpoints (/live, /ready, /health) remain public.
- [Liveness probe](https://docs.tuteliq.ai/api-reference/health/liveness-probe.md): Returns 200 if the service process is running. Use for Kubernetes liveness probe.
- [Readiness probe](https://docs.tuteliq.ai/api-reference/health/readiness-probe.md): Returns 200 if the service is ready to accept traffic. Checks critical dependencies.
- [API landing page](https://docs.tuteliq.ai/api-reference/status/api-landing-page.md): Returns an HTML landing page for browsers or a JSON summary for API clients (curl, Postman). Includes links to documentation, dashboard, and current operational status.
- [Get API status and component health](https://docs.tuteliq.ai/api-reference/status/get-api-status-and-component-health.md): Returns overall API status, component-level health (API, database, cache, AI engine), uptime percentages for the last 24h/7d/30d, and any active incidents. Use for status dashboards and monitoring.
- [Embeddable HTML status page](https://docs.tuteliq.ai/api-reference/status/embeddable-html-status-page.md): Returns a self-contained HTML status page showing component health, uptime percentages, and incident history. Auto-refreshes every 60 seconds. Can be embedded in an iframe on your own status page.
- [Simple ping for external monitors](https://docs.tuteliq.ai/api-reference/status/simple-ping-for-external-monitors.md): Lightweight endpoint returning a minimal OK response. Designed for UptimeRobot, Pingdom, and similar monitoring services that just need a 200 response.
- [List components available for granular pings](https://docs.tuteliq.ai/api-reference/status/list-components-available-for-granular-pings.md): Returns the list of components exposed at `/status/ping/<component>`.
- [Per-component health ping](https://docs.tuteliq.ai/api-reference/status/per-component-health-ping.md): Returns 200 if the named component is healthy, 503 otherwise. Designed for UptimeRobot, Pingdom and similar. Probe results are cached for ~20 seconds to avoid hammering upstream services when multiple monitors poll.
- [Delete mcp](https://docs.tuteliq.ai/api-reference/delete-mcp.md)
- [Get well knownoauth authorization server](https://docs.tuteliq.ai/api-reference/get-well-knownoauth-authorization-server.md)
- [Get well knownoauth protected resource](https://docs.tuteliq.ai/api-reference/get-well-knownoauth-protected-resource.md)
- [Get well knownoauth protected resourcemcp](https://docs.tuteliq.ai/api-reference/get-well-knownoauth-protected-resourcemcp.md)
- [Get mcp](https://docs.tuteliq.ai/api-reference/get-mcp.md)
- [Get mcpsse](https://docs.tuteliq.ai/api-reference/get-mcpsse.md)
- [Get oauthauthorize](https://docs.tuteliq.ai/api-reference/get-oauthauthorize.md)
- [Post mcp](https://docs.tuteliq.ai/api-reference/post-mcp.md)
- [Post mcpmessages](https://docs.tuteliq.ai/api-reference/post-mcpmessages.md)
- [Post oauthauthorize](https://docs.tuteliq.ai/api-reference/post-oauthauthorize.md)
- [Post oauthregister](https://docs.tuteliq.ai/api-reference/post-oauthregister.md)
- [Post oauthtoken](https://docs.tuteliq.ai/api-reference/post-oauthtoken.md)
- [Get a signed liveness challenge nonce with randomized sequence](https://docs.tuteliq.ai/api-reference/age-verification/get-a-signed-liveness-challenge-nonce-with-randomized-sequence.md): Returns a server-signed nonce and a randomized challenge sequence. The client must follow the prescribed order.
- [Get age verification mode configuration](https://docs.tuteliq.ai/api-reference/age-verification/get-age-verification-mode-configuration.md): Returns the verification mode (full or liveness_only) and age threshold for the authenticated user. Pass `country` (ISO 3166-1 alpha-2) and optionally `region` to get market-specific overrides.
- [Retrieve a past age verification result](https://docs.tuteliq.ai/api-reference/age-verification/retrieve-a-past-age-verification-result.md): Returns the age bracket, is_minor status, and verification metadata. No PII returned.
- [Submit documents for age verification](https://docs.tuteliq.ai/api-reference/age-verification/submit-documents-for-age-verification.md): Privacy-first age verification. Returns only age bracket (18+, 13-17, under_13), is_minor status, liveness, and face match. No PII (name, DOB, document number) is returned.
- [Validate a document image (per-step validation)](https://docs.tuteliq.ai/api-reference/age-verification/validate-a-document-image-per-step-validation.md): Checks image quality (resolution, luminance, contrast) without running OCR. Free — no credits consumed.
- [Validate a selfie image (per-step validation)](https://docs.tuteliq.ai/api-reference/age-verification/validate-a-selfie-image-per-step-validation.md): Checks if a face is detected in the image. Free — no credits consumed.
- [Bootstrap a wallet device via App Attest](https://docs.tuteliq.ai/api-reference/wallet/bootstrap-a-wallet-device-via-app-attest.md): Issues a short-lived JWT scoped to verify:submit. The iOS Tuteliq Wallet calls this once at first launch and re-uses the token until it nears expiry. Per-device rate limiting prevents bootstrap abuse.
- [Fetch the Tuteliq prescreen lexicon](https://docs.tuteliq.ai/api-reference/prescreen/fetch-the-tuteliq-prescreen-lexicon.md): Returns the current SDK-side prescreen lexicon: a set of high-precision phrase patterns mapped to category flags. SDKs run this client-side before calling detection endpoints — clearly-benign content can short-circuit the API call entirely, and positive signals can be attached to the request as stru…
- [Cancel a verification session](https://docs.tuteliq.ai/api-reference/verification/cancel-a-verification-session.md): Cancels an active verification session. The mobile device will be notified via SSE.
- [Get a signed liveness challenge nonce](https://docs.tuteliq.ai/api-reference/verification/get-a-signed-liveness-challenge-nonce.md): Returns a server-signed nonce that must be included in the liveness token. This prevents client-side forgery of liveness tokens.
- [Get verification session status](https://docs.tuteliq.ai/api-reference/verification/get-verification-session-status.md): Returns the current status and outcome of a verification session. Only the API key that created the session can access it. The result carries the verification decision (status, age, is_minor, match/liveness/confidence signals) — never extracted document data (name, date of birth, document number), w…
- [Subscribe to session status updates via SSE](https://docs.tuteliq.ai/api-reference/verification/subscribe-to-session-status-updates-via-sse.md): Server-Sent Events stream that emits status changes and results for a verification session. No authentication required — session ID is unguessable (128-bit entropy).
- [Resolve verification mode and language for end-user](https://docs.tuteliq.ai/api-reference/verification/resolve-verification-mode-and-language-for-end-user.md): Called by the HTML verification page on load. Detects the end-user country from IP, resolves the verification mode from market config, and returns the UI language. No authentication required — session ID is unguessable (128-bit entropy).
- [Retrieve a past verification result](https://docs.tuteliq.ai/api-reference/verification/retrieve-a-past-verification-result.md): Get the result of a previous age verification by its ID. Only the owning API key can retrieve its own verifications.
- [Composite non-LLM image verification](https://docs.tuteliq.ai/api-reference/verification/composite-non-llm-image-verification.md): Run a configurable set of forensic checks over a single image in one call: face matching against a reference image, age estimation, NSFW/skin-exposure forensics, and synthetic-image detection (deep-image classifier + C2PA provenance). All checks are deterministic/model-based — no LLM ever sees the i…
- [Create a cross-device verification session](https://docs.tuteliq.ai/api-reference/verification/create-a-cross-device-verification-session.md): Creates a session that can be used to complete verification on another device (e.g. mobile). Both `mode=age` and `mode=identity` require Assure or above. Returns a session ID and mobile URL with a one-time token.
- [Report verification step progress from mobile](https://docs.tuteliq.ai/api-reference/verification/report-verification-step-progress-from-mobile.md): Used by mobile device to report which step the user is on, so desktop can show real-time progress.
- [Submit verification via session (mobile)](https://docs.tuteliq.ai/api-reference/verification/submit-verification-via-session-mobile.md): Complete a verification using a session token. When validate-document and validate-selfie already processed the document and the selfie for this session, this request needs no images at all and returns immediately. Otherwise send the selfie and liveness capture (and, unless validate-document process…
- [Validate and process a document image via session (mobile)](https://docs.tuteliq.ai/api-reference/verification/validate-and-process-a-document-image-via-session-mobile.md): Per-step document validation for the cross-device flow. Checks image quality, then runs the document work (text extraction, face template) so that the submit step does not need the document image again: the session carries the result, never the image, until the session is submitted, cancelled, or ex…
- [Validate and assess a selfie via session (mobile)](https://docs.tuteliq.ai/api-reference/verification/validate-and-assess-a-selfie-via-session-mobile.md): Per-step selfie validation for the cross-device flow. Always checks that a face is present. When the request also carries the liveness capture (`liveness_frame` files and the `liveness_token` field), it runs the selfie assessment now (liveness, age estimation, and the face match against the document…
- [Submit documents for age verification](https://docs.tuteliq.ai/api-reference/verification/submit-documents-for-age-verification.md): Upload ID front, ID back, optional passport, and a selfie with liveness token for age verification. Returns verification result including age, face match, and liveness status.
- [Retrieve a past identity verification result](https://docs.tuteliq.ai/api-reference/identity-verification/retrieve-a-past-identity-verification-result.md): Returns full identity verification data. Business/Enterprise only.
- [Submit documents for identity verification](https://docs.tuteliq.ai/api-reference/identity-verification/submit-documents-for-identity-verification.md): Full KYC identity verification. Returns full name, date of birth, document type, country code, liveness, and face match. Available on Business and Enterprise plans only.
- [Validate a document image (per-step validation)](https://docs.tuteliq.ai/api-reference/identity-verification/validate-a-document-image-per-step-validation.md): Checks image quality (resolution, luminance, contrast) without running OCR. Free — no credits consumed.
- [Validate a selfie image (per-step validation)](https://docs.tuteliq.ai/api-reference/identity-verification/validate-a-selfie-image-per-step-validation.md): Checks if a face is detected in the image. Free — no credits consumed.
- [Get anonymised global risk trends](https://docs.tuteliq.ai/api-reference/risk-profile/get-anonymised-global-risk-trends.md): Returns aggregated, fully anonymised risk signal trends across all customers. No PII is stored or returned. Available to Business tier and above.
- [Get emerging threats](https://docs.tuteliq.ai/api-reference/threat-intelligence/get-emerging-threats.md): Identifies threat categories with rapid growth (>50% week-over-week increase). Useful for early warning systems and proactive safety measures. All data is anonymised and k-anonymity is enforced.
- [Get anonymised threat intelligence trends](https://docs.tuteliq.ai/api-reference/threat-intelligence/get-anonymised-threat-intelligence-trends.md): Returns aggregated, anonymised detection trends across all customers. Includes breakdowns by endpoint, category, age group, platform, and language. All data is k-anonymised — buckets with fewer than 5 signals are suppressed. No PII or customer-identifiable information is ever included.
- [Get weekly threat intelligence digest](https://docs.tuteliq.ai/api-reference/threat-intelligence/get-weekly-threat-intelligence-digest.md): Returns a pre-formatted weekly summary suitable for email or Slack notifications. Includes top threats, emerging categories, and notable trends. All data is anonymised with no PII.
- [Delete a policy rule](https://docs.tuteliq.ai/api-reference/policy-rules/delete-a-policy-rule.md): Permanently delete a policy rule.
- [List all policy rules](https://docs.tuteliq.ai/api-reference/policy-rules/list-all-policy-rules.md): Returns all policy rules for the authenticated user, sorted by priority (ascending).
- [Get a policy rule](https://docs.tuteliq.ai/api-reference/policy-rules/get-a-policy-rule.md): Retrieve a specific policy rule by ID.
- [Create a policy rule](https://docs.tuteliq.ai/api-reference/policy-rules/create-a-policy-rule.md): Create a new declarative policy rule. Rules are evaluated during detection and the highest-priority matching rule determines the policy_action in the response.
- [Test-evaluate policy rules](https://docs.tuteliq.ai/api-reference/policy-rules/test-evaluate-policy-rules.md): Evaluate your policy rules against a mock detection result. Useful for testing rules before going live.
- [Update a policy rule](https://docs.tuteliq.ai/api-reference/policy-rules/update-a-policy-rule.md): Update an existing policy rule. Partial updates are supported.
- [Reset detection settings to defaults](https://docs.tuteliq.ai/api-reference/settings/reset-detection-settings-to-defaults.md): Remove all custom detection settings. All endpoints will be active.
- [Get detection settings](https://docs.tuteliq.ai/api-reference/settings/get-detection-settings.md): Get your account-level detection settings. These control which detection endpoints are active for your account. Disabled endpoints are automatically skipped in /analyse/multi and return not_detected on individual calls.
- [Update detection settings](https://docs.tuteliq.ai/api-reference/settings/update-detection-settings.md): Configure which detection endpoints are active for your account. Use `enabled_endpoints` (whitelist — only these run) OR `disabled_endpoints` (blacklist — these are skipped). Cannot use both.
- [Fetch an EU AI Act Art 12 audit receipt](https://docs.tuteliq.ai/api-reference/audit/fetch-an-eu-ai-act-art-12-audit-receipt.md): Returns the signed audit receipt for a past inference. Only the deployer that produced the receipt can fetch it (api-key fingerprint match enforced; non-matches return 404 to avoid existence leaks). Receipts are signature-verified before return; tampered storage triggers a 500 with code AUDIT_RECEIP…
- [List the caller's incidents (newest first, paginated)](https://docs.tuteliq.ai/api-reference/incidents/list-the-callers-incidents-newest-first-paginated.md): Read-only paginated listing of incidents recorded under this API key's account. Each row is non-PII metadata by default; pass `include_summary=true` to include the decrypted incident summary (extra credits per row). BYOK incidents return the hybrid envelope on the summary field and list the field na…
- [KPI overview of incidents in a time window](https://docs.tuteliq.ai/api-reference/incidents/kpi-overview-of-incidents-in-a-time-window.md): Counts by category, severity, source, and status, plus top platforms and 24h/7d/30d totals. Defaults to the last 30 days. Read-only; no LLM call.
- [Time-series buckets of incident volume](https://docs.tuteliq.ai/api-reference/incidents/time-series-buckets-of-incident-volume.md): Returns time-bucketed counts of incidents (with per-bucket severity breakdown). Bucket sizes: hour, day (default), week. Useful for rendering trend charts in dashboards.
- [Get the full detail for a single incident (read-only)](https://docs.tuteliq.ai/api-reference/incidents/get-the-full-detail-for-a-single-incident-read-only.md): Returns the full incident document for the caller's account. Server-encrypted fields (summary, metadata, source_data) are decrypted server-side. BYOK fields are returned as hybrid envelopes for client-side decryption — see `_e2e_envelope_fields` in the response for which to decrypt locally. 404 if t…
- [Submit the same moderator review across multiple incidents (Art 14, bulk)](https://docs.tuteliq.ai/api-reference/incidents/submit-the-same-moderator-review-across-multiple-incidents-art-14-bulk.md): Applies the same review action + reason to up to 100 incidents in one call. Each incident emits its own signed Art 12 audit receipt — bulk is a UX shortcut, not a compliance shortcut. Per-incident success/error is returned so a partial failure can be retried without re-running successful items.
- [Submit a moderator review of an incident (Art 14 human oversight)](https://docs.tuteliq.ai/api-reference/incidents/submit-a-moderator-review-of-an-incident-art-14-human-oversight.md): Records a deployer-side moderator decision (confirm / downgrade / escalate / reclassify / dismiss) on a model-produced incident. The override is persisted to the incident document and a separate signed Art 12 audit receipt is emitted linking back to the original. The optional reason_comment is encry…
- [List the org's device fleet with a compliance summary](https://docs.tuteliq.ai/api-reference/agent/list-the-orgs-device-fleet-with-a-compliance-summary.md): Returns every device's latest attestation for the caller's org (newest first) plus a rollup summary (total / compliant / non-compliant / compliance %). Read-only, deterministic, no LLM. Scoped to the API key's org.
- [Get a single device's latest attestation](https://docs.tuteliq.ai/api-reference/agent/get-a-single-devices-latest-attestation.md): Returns the latest attestation for one device in the caller's org. 404 if the device has never checked in (or belongs to another org).
- [Report a device attestation (endpoint agent check-in)](https://docs.tuteliq.ai/api-reference/agent/report-a-device-attestation-endpoint-agent-check-in.md): The tuteliq-agent CLI evaluates the org's device-safety policy locally and reports the pass/fail result here. One latest-state record is kept per device (upsert, no history). The org is derived from the authenticated API key — any org_id in the body is ignored. No user content is stored; only device…

## OpenAPI Specs

- [openapi](/openapi.json)

## Optional

- [API Status](https://tuteliq.ai/status)
- [Dashboard](https://tuteliq.ai/dashboard)


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