Effective January 1, 2025 · Version 1.0 (Seed Edition) · Part 2 of 2
1. Privacy Philosophy
1.1 Privacy as Architecture, Not Afterthought. MoV was not designed first and made private later. Privacy is embedded in every architectural decision the Platform makes — from how voice is processed (ephemerally, not archived) to how emotional data is stored (as structured features, not raw recordings) to how AI models are trained (on anonymized patterns, not identifiable personal histories). Privacy-by-design is not a compliance posture at MoV. It is the engineering standard against which every system decision is evaluated.
1.2 The Five Foundational Privacy Principles
01 · Data Minimization
MoV collects only the data required to deliver specific, defined product functions. No data is collected speculatively, for future monetization purposes, or because it might be useful eventually. Every data point has a stated purpose. If the purpose is removed, the data is deleted.
02 · Ephemeral Voice Processing
Raw voice recordings are transient by design. They exist in MoV's systems only for the duration of processing — a maximum of 24–48 hours — after which they are permanently and irreversibly deleted. MoV's value comes from the intelligence derived from voice, not from the retention of voice itself.
03 · User-Controlled Data Ownership
Users own their data on MoV. The Platform holds data in trust, as a processing agent, not as an owner. Users can access, correct, export, restrict, and delete their data at any time, subject to the operational constraints outlined in this Policy.
04 · Purpose Limitation
Data collected for one purpose is not repurposed for another without explicit additional consent. Voice collected for HCP construction is not used for advertising. Emotional patterns detected for mediation are not shared with commercial partners. Every use case is bounded at the point of collection.
05 · Transparency Over Opacity
MoV tells users exactly what is being collected, how it is processed, how long it is retained, and who may access it — in plain language, not buried in footnotes. AI processing is disclosed, not hidden. When the Platform does not know something with certainty (such as the perfect accuracy of emotion detection), it says so.
MoV Does Not
1. Use data for advertising targeting of any kind 2. Build behavioral profiles for commercial sale 3. Monetize engagement patterns or emotional states 4. Use surveillance-style continuous data harvesting 5. Apply dark patterns to extract unnecessary consent 6. Retain raw voice beyond 48 hours post-processing
MoV Does
1. Process voice ephemerally and delete promptly 2. Store only derived, structured intelligence features 3. Give users granular control over AI participation 4. Apply AES-256 encryption to all stored data 5. Disclose AI processing in plain, explicit language 6. Delete all personal data within 30 days of request
2. Data Categories Collected
MoV collects four primary categories of data. Each category is collected only to the extent necessary for the specific product functions it enables. The following breakdown defines each category, what it includes, and what it is used for.
Category 2.1 · Identity & Preference Data
1. Name and display name 2. Date of birth / age range 3. Location (city-level granularity; precise GPS not required) 4. Relationship type preferences (romantic, social, shared-interest) 5. Basic demographic attributes provided at registration 6. Subscription tier and payment identifiers (processed by third-party payment provider; card details never held by MoV)
Category 2.2 · Voice & Acoustic Data
1. Raw audio recordings (temporary; max 24–48 hrs) 2. Derived acoustic features: pitch profile, speech rate, vocal energy, prosodic rhythm, pause patterns 3. Voice embeddings (mathematical vector representations; non-reversible to audio) 4. Language and accent region (detected, not user-declared) 5. Audio quality metrics (signal-to-noise ratio, clarity scores)
Category 2.3 · Emotional & Behavioral Data
1. Emotion signal classifications (joy, comfort, tension, anxiety, curiosity, excitement, withdrawal) 2. Conversation dynamics (talk-time balance, topic resonance, reciprocity ratios) 3. Interaction patterns (call frequency, duration trends, session timing) 4. Relational motive signals derived from conversation context 5. Post-call engagement signals (rating inputs, feedback responses)
Category 2.4 · AI-Inferred Relational Data
1. Human-Connect Profile (HCP) dimensions: personality structure, communication style, attachment tendency, bonding style 2. Compatibility vectors: multi-dimensional scores generated by matching algorithm 3. Motive alignment indicators: outputs of the 24-Motive Intent Model 4. Longitudinal bonding trajectory estimates 5. Trust and comfort curve modeling
Important Distinction: Categories 2.3 and 2.4 contain data that may qualify as sensitive personal data under GDPR Article 9 (special categories) or DPDP Act 2023 provisions on inferred sensitive attributes. MoV processes this data only under explicit consent and applies heightened technical and organizational protections to all such data.
3. How Data Is Used
3.1 Core Platform Functions. All data processing by MoV is directed toward one of the following core platform functions. No data is processed for purposes outside this list without new explicit consent: 1. Human-Connect Profile (HCP) construction and maintenance: Voice, behavioral, and emotional data is synthesized to build each user's dynamic relational identity model, which is the foundational intelligence layer enabling all other Platform functions. 2. Compatibility matching: HCP vectors, acoustic feature embeddings, and motive alignment signals are used to surface connection candidates with meaningful relational compatibility — not superficial categorical similarity. 3. Real-time AI mediation: Emotional signals, conversation dynamics, and HCP attributes are processed live during voice interactions to generate Mediator Engine outputs — nudges, safety alerts, topic suggestions, and pacing guidance. 4. Post-interaction insight generation: Counsel Engine analysis of recorded interaction patterns produces emotional resonance summaries, bonding trajectory indicators, and communication coaching feedback. 5. Safety and fraud prevention: Behavioral signals, device metadata, and voice biometrics are processed continuously to detect and respond to conduct violations, impersonation, underage access, and platform abuse. 6. Service delivery and support: Identity and preference data is used to manage user accounts, process subscriptions, and deliver customer support — handled by authorized personnel only.
3.2 System Learning & Model Improvement. MoV's AI systems improve over time through exposure to aggregated interaction patterns. Data used for system learning is subject to the following strict constraints: 1. Only anonymized and aggregated data is used for model training. Individual user data is never directly input into training pipelines without cryptographic de-identification. 2. Voice recordings are never used for model training in raw audio form. Only derived acoustic features — extracted during processing and stripped of personally identifiable attributes — may be retained for model improvement purposes. 3. Users may opt out of contributing their interaction patterns to model improvement without affecting their access to Platform features. Opt-out is available through privacy settings. 4. Model improvement processing does not create new inferences about identifiable individuals. It refines aggregate pattern detection capabilities across the user population.
4. Voice Data Handling
Critical Architecture Principle: Voice is a transient input signal on MoV — not a stored identity asset. The Platform's value comes entirely from the structured intelligence derived from voice, not from retaining the recordings themselves. This distinction is foundational and non-negotiable.
4.1 Voice Data Lifecycle
Voice Processing Data Lifecycle
1. Capture (t = 0): Audio recorded client-side via encrypted WebRTC session. 2. Process (< 2 seconds): Whisper STT + OpenSmile feature extraction + emotion scoring. 3. Store (max 48 hours): Raw audio held in encrypted temporary storage pending QA. 4. Delete (Auto-triggered): Raw audio permanently deleted; derived features persist in HCP. 5. Retain (Until deletion request): Structured features, embeddings & HCP stored encrypted long-term.
4.2 Raw Audio — Handling Rules. 1. Raw audio recordings are stored in encrypted temporary storage for a maximum of 24–48 hours following initial processing — solely to support quality assurance verification and processing error correction. 2. No raw audio recording is retained beyond 48 hours under any operational circumstance, unless the user has provided separate, explicit consent for extended retention (for example, to preserve a specific conversation they have chosen to archive). 3. Raw audio is never accessed by human reviewers except in formal moderation proceedings where a safety or conduct violation has been flagged through the Platform's reporting system — and only with documented authorization under the Platform's moderation governance framework. 4. Raw audio is never used as a training asset in any AI model — regardless of consent status.
4.3 Derived Voice Features — Handling Rules. 1. Derived features — acoustic measurements, voice embeddings, emotional signal scores — are retained as part of the user's HCP for the duration of their active account. 2. Voice embeddings are mathematical vector representations of vocal patterns. They cannot be reversed to reconstruct original audio. They are not voice recordings. 3. Derived features are encrypted at rest using AES-256 and transmitted only over TLS-secured channels. 4. Upon account deletion, all derived voice features are cryptographically shredded within 30 days and cannot be recovered following this process.
4.4 Conversation Transcripts — Handling Rules. 1. Speech-to-text transcripts generated during voice processing are stored in encrypted form, linked to the user's session record. 2. Default transcript retention period: 90 days, after which transcripts are automatically deleted unless the user has elected extended retention through their privacy settings. 3. Transcripts are accessible only to the individual user (through data export) and to Platform safety teams in formal moderation proceedings. 4. Transcripts are not shared with the other participant(s) in a conversation unless both parties have explicitly consented to transcript sharing as part of a specific Platform feature.
User Acknowledgment — Voice Data
By submitting voice inputs to MoV, you understand and accept that: raw audio will be deleted within 48 hours of processing; derived features will be retained as part of your HCP; your voice cannot be reconstructed from stored embeddings; and all voice-derived data will be permanently deleted within 30 days of account closure or an explicit data deletion request.
5. Emotion Analytics & AI Processing
5.1 How Emotion Detection Works. MoV's Emotional Intelligence Engine (EIE) analyzes voice inputs through a layered approach that combines acoustic feature analysis, linguistic pattern recognition, and contextual AI interpretation. This process does not read minds — it identifies measurable patterns in voice signals that correlate with specific emotional states, as validated through established psychoacoustic research. The analytical pipeline operates as follows: acoustic features (pitch, energy, rate, rhythm, spectral characteristics) are extracted using signal processing libraries; these features are fed into trained classification models that assign probabilistic scores to a defined set of emotional states; scores are interpreted in context — accounting for the user's baseline vocal profile established in their HCP, the conversational context of the interaction, and the accumulated pattern of the session.
5.2 Emotional States Analyzed. The EIE is calibrated to detect and score the following emotional states as they manifest in voice during Platform interactions: 1. Warmth & openness: Indicators of positive emotional availability and engagement readiness. 2. Comfort & ease: Relaxation markers, reduced tension signals, natural conversational rhythm. 3. Curiosity & interest: Engagement energy, question patterns, active listening markers. 4. Excitement & enthusiasm: Vocal energy surges, positive inflection, accelerated pacing. 5. Tension & stress: Vocal tightening, irregular pacing, micro-pauses, pitch elevation. 6. Withdrawal & discomfort: Energy reduction, shortened responses, rhythm disruption. 7. Emotional reciprocity: Balance and synchrony in emotional energy between conversation participants.
5.3 Mandatory Disclaimers — Accuracy & Limitations
Emotion Detection is Probabilistic, Not Definitive. MoV's EIE generates probability-weighted interpretations of emotional state signals — not clinical diagnoses, psychological assessments, or factual determinations of how a person feels. No AI system can read human emotion with perfect accuracy. MoV's models have documented limitations and are continuously improved, but they will never be error-free.
Known sources of variation and potential misclassification include: 1. Language and linguistic diversity: Emotion detection models perform with higher accuracy in languages and dialects with stronger training data representation. Accuracy for under-represented languages may be materially lower. 2. Accent and regional speech patterns: Acoustic features associated with specific emotional states vary significantly across regional accents and speech communities. The Platform is actively expanding training data to reduce accent-based bias. 3. Cultural expression norms: Emotional expression is culturally mediated. What registers as enthusiasm in one cultural context may register differently in the model's output for another. MoV acknowledges this limitation and incorporates cultural context calibration where data supports it. 4. Individual baseline variation: The EIE calibrates against each user's personal vocal baseline established through HCP construction. Early-stage HCPs (limited interaction history) will produce less accurate emotional inferences than mature HCPs. 5. Neurodiversity and atypical speech patterns: Users whose speech patterns differ from neurotypical norms may experience reduced accuracy in emotion detection outputs. MoV is committed to improving model inclusivity across neurodiverse communication styles.
6. Data Storage & Security
6.1 Encryption Standards. 1. At rest: All personal data — including HCP attributes, voice features, emotional signal scores, and transcript data — is encrypted using AES-256-GCM with keys managed through a dedicated secrets management system. Encryption keys are rotated on a regular schedule and are never co-located with the data they protect. 2. In transit: All data transmitted between client applications and MoV's servers — including real-time voice streams, AI mediation outputs, and user profile data — is encrypted using TLS 1.3 or higher. End-to-end encryption is applied to peer-to-peer voice communications via WebRTC. 3. Voice streams: Live voice call audio is transmitted peer-to-peer over encrypted WebRTC channels. Audio chunks processed by the AI mediation pipeline are encrypted in transit to and from processing services under strict data processing agreements.
6.2 Infrastructure Architecture. 1. MoV operates on a cloud infrastructure stack combining Vercel Edge Functions for API processing, Supabase PostgreSQL for structured data storage, and Pinecone vector database for embedding storage — all deployed under dedicated security configurations. 2. Data architecture is segmented: voice processing services, HCP storage, analytics infrastructure, and administrative systems operate in separate logical environments with controlled inter-service communication. 3. All production infrastructure is deployed in data centers with SOC 2 Type II certification or equivalent security assurance. Primary storage is hosted in us-east-1 (US) with replication to eu-west-1 (Europe) for disaster recovery, subject to applicable data residency requirements.
6.3 Access Controls. 1. Role-based access control (RBAC): Internal access to user data is restricted to personnel with a documented, job-function-specific need. Access levels are defined across four roles: user (self-access only), support (limited account data), moderator (safety-relevant content access), and admin (system configuration, no bulk data access). 2. Access logging & audit trails: All internal access to personal data is logged with timestamp, user identity, data category accessed, and stated purpose. Logs are retained for a minimum of 12 months and are reviewed in periodic security audits. 3. Multi-factor authentication: All internal system access by MoV personnel requires multi-factor authentication. Administrative access to production systems requires hardware-key MFA. 4. Penetration testing: The Platform undergoes independent security penetration testing no less than annually and following any material architectural change. Test outcomes inform a structured remediation process.
6.4 Breach Response. In the event of a confirmed personal data breach that creates risk of harm to affected users, MoV will: notify affected users within 72 hours of confirmed breach identification; report to the applicable data protection authority within the legally required timeframe; take immediate containment action; and provide affected users with detailed information about the nature of the breach, data categories affected, and recommended protective actions.
7. Data Retention Policy
MoV's retention policy follows a purpose-expiry model: data is retained only for as long as required to fulfill the specific function for which it was collected. The following table defines retention periods by data category:
1. Raw audio recordings | Retention: 24–48 hours maximum post-processing | Trigger: Automatic; time-based | Status: Auto-deleted 2. Conversation transcripts | Retention: 90 days default; user-configurable (30–365 days) | Trigger: Scheduled; or user request | Status: User-controlled 3. Derived voice features / embeddings | Retention: Duration of active account | Trigger: Account closure or deletion request | Status: Account-linked 4. Human-Connect Profile (HCP) | Retention: Duration of active account | Trigger: Account closure or deletion request | Status: Account-linked 5. Emotional signal history | Retention: Duration of active account; limited to 12 months per interaction session | Trigger: Rolling 12-month window; or account closure | Status: Rolling window 6. Match & interaction history | Retention: Duration of active account | Trigger: Account closure or deletion request | Status: Account-linked 7. Aggregated analytics data | Retention: Indefinite (anonymized; no individual identification possible) | Trigger: Not individually deletable once anonymized | Status: Anonymized 8. Safety & moderation records | Retention: 24 months following resolution of incident | Trigger: Scheduled; subject to legal hold where applicable | Status: Compliance hold 9. Device & access logs | Retention: 12 months | Trigger: Scheduled; automatic rolling deletion | Status: Auto-rolled 10. All personal data (post account deletion) | Retention: 30 days post-deletion request | Trigger: Account closure confirmation | Status: Final deletion
Legal Hold Exception: Where personal data is subject to a legal hold — for example, as evidence in an active law enforcement investigation or litigation — standard retention periods are suspended for the duration of the hold. Users will be notified of legal holds affecting their data to the extent permitted by applicable law.
8. User Rights
MoV recognizes and upholds the following data subject rights under applicable privacy law frameworks. These rights are exercisable through the Platform's Privacy Controls interface or by submitting a formal request through the privacy request channel.
Right of Access
Request a complete copy of all personal data MoV holds about you, including HCP attributes, voice-derived features, emotional signal history, and interaction records.
Right of Correction
Request correction of inaccurate identity or preference data. Note: AI-inferred HCP attributes are model outputs and cannot be manually overridden; they update through ongoing interaction.
Right of Erasure
Request permanent deletion of all personal data. Erasure requests are processed within 30 days. Anonymized data from which you cannot be re-identified is not subject to erasure.
Right of Portability
Export your personal data in a structured, machine-readable format (JSON). Includes profile data, interaction summaries, and HCP dimension scores — but not raw audio (deleted prior to any export request).
Right of Restriction
Request that MoV restrict processing of your data to storage only — for example, while you contest the accuracy of data or object to its use — pending resolution of your concern.
Control AI Participation
Configure the level of AI involvement in your interactions — including emotion detection depth, mediation intensity, and contribution to model training. Safety-critical monitoring cannot be fully disabled.
8.1 Exercising Your Rights. Rights requests are processed within the timelines required by applicable law — typically 30 days for GDPR and DPDP Act 2023 regulated requests, with a single 30-day extension available for complex requests. MoV does not charge fees for rights requests except where requests are manifestly unfounded or repetitive. Identity verification is required before any rights request is actioned. Users will receive written confirmation of the outcome of every rights request.
9. Consent Framework
9.1 Consent Architecture. MoV's consent system is built on three structural principles that govern every consent interaction on the Platform:
Explicit — No Implied Consent
Consent on MoV is always affirmative — a positive, deliberate action by the user. No processing category is activated by default, by inaction, or by implied agreement to platform-wide terms. Each consent is obtained at the point at which the relevant processing begins — not in advance of the user's first interaction with that function.
Granular — Feature-Level Control
Consent is collected at the level of specific processing activities — not as a single blanket authorization for all Platform processing. Users consent to voice analysis, emotion detection, AI mediation, and model contribution independently. Refusing consent for non-essential categories does not affect access to the core Platform.
Revocable — Withdraw Anytime Without Penalty
Consent may be withdrawn at any time through the Privacy Controls interface without any penalty to the user's account standing or access to features that do not depend on the withdrawn processing category. Withdrawal does not affect the lawfulness of processing that occurred before withdrawal. Where withdrawal affects a feature, the user is clearly informed of this before withdrawal is confirmed.
9.2 Consent Categories. 1. Voice analysis consent: Required for all core Platform functions. Covers acoustic feature extraction and HCP construction from voice inputs. Cannot be refused without foregoing Platform access, as voice analysis is the foundational service layer. 2. Emotion detection consent: Required for Mediator Engine, Counsel Engine, and compatibility scoring functions. Users who withdraw emotion detection consent will experience reduced AI insight quality and mediation capability. 3. AI mediation consent: Governs delivery of real-time nudges and conversational guidance during voice interactions. Safety-critical discomfort detection and boundary violation alerting remain active regardless of mediation consent status. 4. Model training contribution consent: Optional. Governs whether anonymized interaction patterns from this user's sessions are used to improve AI models. Refusal or withdrawal has no effect on the user's access to any Platform feature. 5. Extended transcript retention consent: Optional. Governs whether transcripts are retained beyond the 90-day default. Users may elect retention periods of up to 365 days if desired.
10. Data Sharing
Fundamental Position: MoV does not sell user data. MoV does not share user data with advertisers. MoV does not provide user data to commercial partners for targeting, profiling, or monetization purposes of any kind. This is not a compliance position — it is a product architecture decision that is incompatible with MoV's revenue model and platform mission.
10.1 Permitted Data Sharing. MoV shares user data only in the following circumstances, each of which is bounded by strict technical and contractual controls: 1. Infrastructure service providers: Data is shared with sub-processors that provide the technical infrastructure on which MoV operates — including cloud hosting (Vercel, Supabase), voice processing (OpenAI Whisper), vector search (Pinecone), real-time communication (LiveKit), and notification delivery (FCM/APNS). Each sub-processor operates under a binding Data Processing Agreement that limits their use of data strictly to the contracted service function. 2. Legal compliance and law enforcement: Data may be disclosed to government authorities, law enforcement agencies, or courts when legally compelled by valid legal process — including warrants, court orders, or regulatory notices. Where permitted by law, MoV will notify affected users prior to disclosure. MoV will challenge overbroad or unlawful data demands. 3. Safety-driven disclosure: In circumstances where disclosure is necessary to prevent imminent harm to a person — including credible threats of violence or self-harm communicated through the Platform — MoV may share relevant data with emergency services or law enforcement without prior user notice, as legally permitted. 4. Anonymized research: MoV may share aggregated, anonymized research outputs — statistical patterns, population-level behavioral insights, or AI model performance metrics — with academic research partners under formal research agreements. No individual user can be identified from research data shared under this category. 5. Business transfers: In the event of a merger, acquisition, or sale of MoV or substantially all of its assets, user data may be transferred to the acquiring entity as part of the transaction. Users will be notified of such transfers with a minimum of 30 days' advance notice and will be provided with the opportunity to request account deletion before the transfer completes.
10.2 Sub-Processor Accountability. MoV maintains a current register of all sub-processors with access to personal data. This register is available to users upon request and is updated within 30 days of any material sub-processor change. All sub-processors are assessed for security posture, privacy compliance, and alignment with MoV's data governance standards prior to engagement and reviewed annually thereafter.
11. AI Ethics & Bias Mitigation
11.1 Commitment to Ethical AI. MoV's AI systems analyze voice patterns, emotional signals, and behavioral data to deliver relational intelligence. This creates ethical obligations that MoV takes seriously and structures into its product governance. The following risks are documented, actively monitored, and systematically mitigated:
Risk 01 — Cultural Bias in Voice Analysis
Emotional expression and vocal communication norms vary significantly across cultures. AI models trained on non-diverse datasets may systematically misclassify emotional states for users from underrepresented cultural backgrounds.
→ Mitigation: Continuous diversification of training datasets across regional, cultural, and linguistic dimensions. Quarterly bias audits comparing model performance across demographic cohorts.
Risk 02 — Accent-Based Misclassification
Acoustic feature extraction models may perform with reduced accuracy for non-standard accents or dialects underrepresented in training data, producing systematically biased emotional inferences for affected users.
→ Mitigation: Accent-stratified model validation. User feedback mechanisms for flagging inaccurate AI outputs. Expanded accent coverage in ongoing training data collection.
Risk 03 — Emotional Misinterpretation
Probabilistic emotion classification carries inherent uncertainty. High-confidence misclassifications — for example, classifying excitement as anxiety — could produce inappropriate mediation outputs that negatively affect the user's interaction experience.
→ Mitigation: Conservative confidence thresholds before mediating on emotion signals. User-configurable emotion sensitivity. Human-in-the-loop escalation for high-stakes safety interventions.
Risk 04 — Feedback Loop Amplification
AI systems that influence user behavior based on behavioral patterns risk reinforcing those same patterns in future model outputs, creating feedback loops that reduce the diversity of relational intelligence produced by the Platform.
→ Mitigation: Anti-loop detection in model training pipelines. Intentional training data diversification. Periodic model output distribution audits to detect convergence bias.
11.2 Human-in-the-Loop Governance. MoV maintains a standing AI ethics review function responsible for: quarterly review of model performance across demographic dimensions; evaluation of new model deployments for bias before production release; investigation of user-reported AI inaccuracy patterns; and annual third-party ethical AI audits. AI systems do not make consequential decisions about users — including account suspensions, safety escalations, or match exclusions — without human review at the decision boundary.
11.3 User Reporting of AI Inaccuracy. Users who believe AI-generated insights, emotion classifications, or mediation outputs are systematically inaccurate for their voice, language, or cultural context can submit an AI Accuracy Report through the Platform's feedback interface. Submitted reports are reviewed by the AI ethics team within 14 business days, and qualifying reports result in flagged review of the user's AI model interactions and potential recalibration of their HCP baseline.
12. Child Safety
Zero Tolerance: MoV does not permit access by any person under the age of 18 under any circumstance. Child safety is not a compliance checkbox — it is an absolute architectural and operational commitment enforced at every layer of the Platform.
12.1 Age Enforcement Architecture. 1. Registration gate: Age verification is required at registration. Users who provide a date of birth indicating they are under 18 are denied registration at the point of submission. 2. Voice-based age signal detection: The AI processing pipeline incorporates vocal age-range estimation as a supplementary signal. Where voice analysis generates a strong signal inconsistent with declared age — particularly where that signal suggests a minor — the account is flagged for immediate safety review. 3. Behavioral anomaly detection: Usage patterns inconsistent with adult behavior — including specific linguistic patterns, interaction characteristics, or session behaviors associated with younger users — trigger automated flagging and safety escalation. 4. Premium Plus identity verification: Users who elect the verified matching pool undergo government ID verification that independently confirms age. Verified status is prominently indicated in the discovery interface.
12.2 Immediate Action Protocol. Upon confirmed or credible suspicion of underage access, MoV takes the following immediate actions: account access is suspended pending investigation; all voice and interaction data associated with the account is preserved and isolated for review; the incident is escalated to MoV's Trust & Safety team within one hour; all personally identifiable data associated with the account is treated as the data of a minor and handled under the strictest applicable child data protection standards; and where legally required, the incident is reported to the applicable child protection authority.
12.3 No Minor Data Retention. If MoV discovers that it has inadvertently collected personal data from a person under 18, all such data is deleted within 24 hours of confirmation. No such data is retained for any purpose, including AI model training, analytics, or safety records, beyond what is required for the incident report itself.
13. International Compliance
13.1 India — Digital Personal Data Protection Act 2023 (DPDP Act). As an India-headquartered platform launching initially in the Indian market, MoV is designed for full compliance with the Digital Personal Data Protection Act 2023. Key alignment points include: processing only on lawful bases (consent-first for all core functions); appointment of a designated Data Protection Officer; robust data principal rights implementation (access, correction, erasure, grievance); purpose and storage limitation architecture; localization-ready infrastructure configuration; and mandatory data breach notification within 72 hours of discovery.
13.2 European Union — General Data Protection Regulation (GDPR). For users accessing MoV from within the European Economic Area, the Platform applies GDPR standards in full, including: lawful basis for processing (Article 6 — consent, legitimate interest for safety functions); explicit consent for special category data processing (Article 9 — emotional inferences, biometric voice features); data subject rights enforcement under Articles 15–22; Data Processing Agreements with all EEA-accessible sub-processors (Article 28); and privacy-by-design and by-default architecture (Article 25). MoV's DPO is the designated contact for GDPR-related requests.
13.3 United States — CCPA and State Privacy Laws. For users in US states with applicable consumer privacy rights — including California (CCPA/CPRA), Virginia (VCDPA), Colorado (CPA), and others — MoV provides equivalent data rights: the right to know, right to delete, right to opt out of data sale (MoV does not sell data), and right to non-discrimination for exercising privacy rights. Users in biometric privacy jurisdictions (Illinois BIPA, Texas TDPPA) are provided with explicit consent flows specific to voice biometric features, including the right to withdraw consent and the right to have biometric identifiers deleted.
13.4 Cross-Border Data Transfers. Where personal data is transferred between jurisdictions — for example, from the EU to the US for AI processing — MoV employs appropriate transfer mechanisms including Standard Contractual Clauses (SCCs) approved by the European Commission and equivalent mechanisms under applicable law. Transfer impact assessments are conducted for all cross-border processing relationships involving personal data of EU data subjects.
14. Privacy Principle
14.1 The Foundational Commitment. The entirety of MoV's privacy architecture — every retention limit, every consent requirement, every encryption standard, every bias audit — exists in service of a single human truth:
The Privacy Principle — Moment of Vibe
Your voice is your identity — not a commodity.
When you speak on MoV, you are not feeding a data engine. You are reaching for another human being — and the Platform exists to make that reach more likely to succeed.
14.2 Privacy as Trust Infrastructure. Privacy at MoV is not a regulatory obligation reluctantly fulfilled. It is the trust foundation on which every feature, every AI system, and every relational outcome depends. Users who do not trust that their voice, their emotions, and their relational patterns are handled with integrity will not be authentic on the Platform. And a platform built on authenticity cannot survive without that trust. Privacy, therefore, is not a constraint on MoV's mission. It is the precondition for it.
Strategic Insights — Why This Privacy Architecture Is Different
Four Fundamental Distinctions
01 · Platform ≠ Social Media
MoV does not operate on an attention economy. There are no feeds to optimize, no engagement metrics to maximize, no addictive interaction loops to sustain. The Platform's success is measured by the quality and depth of connections formed — not by time spent, content consumed, or daily active user counts. Connection Quality → Revenue This structural difference means MoV has no commercial incentive to exploit user attention, emotional vulnerability, or behavioral patterns for engagement purposes. Privacy protections are therefore reinforced by — not in conflict with — the business model.
02 · Data ≠ Ad Asset
MoV's revenue comes entirely from subscription fees and contextual affiliate commissions triggered by user-initiated relational plans — not from advertising. There is no advertising infrastructure, no demand-side platform, no advertiser data-sharing arrangement, and no behavioral targeting apparatus in MoV's technical stack. User Data → Connection Intelligence Only Emotional data, voice features, and relational patterns are processed to serve the user who generated them — not to serve a commercial partner who wants to reach them. This is a categorical difference from ad-supported social and dating platforms.
03 · AI ≠ Control System
MoV's AI systems are designed to illuminate — not to direct. They surface emotional patterns, suggest conversational pathways, and flag safety risks. They do not decide who connects, how relationships develop, or what outcomes users pursue. AI Assists → Human Agency Preserved User autonomy is the non-negotiable boundary around every AI function. No nudge is mandatory. No insight is authoritative. No AI recommendation overrides the user's own judgment about their relational life. The AI advises — the human decides.
04 · Privacy = Core Product Feature
On most platforms, privacy is what the legal team adds after the product team finishes. On MoV, privacy is what makes the product work. Users will only speak openly, authentically, and with emotional vulnerability if they trust that what they share is protected. Privacy → Authenticity → Connection Quality This means every privacy protection in this Policy — every retention limit, consent requirement, and encryption standard — is simultaneously a product decision. Privacy is the infrastructure that makes genuine human connection on a digital platform possible.
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