Privacy Policy

Prefatory Declaration

This Privacy Codex ("the Codex," "the Instrument," "the Juridical Superstructure") articulates, with extreme conceptual density and maximal terminological granularity, the doctrines governing the acquisition, modulation, algorithmic transfiguration, custodial retention, infrastructural mobilization, and terminal dissolution of informational constructs emanating from your interaction with Airaa ("the Application," "the Entity," "we," "our," or "us").

Engagement with the Application signifies complete, unmitigated assent to the epistemic, operational, and jurisprudential tenets embedded herein.

1. Ontological Classification of Data Constellations

The Application may, through voluntary user propulsion, passive system telemetry, or autonomous algorithmic inference, assimilate a diverse matrix of informational artifacts, categorized as follows:

1.1 Volitionally Submitted Semiotic Constructs

• Textual discourse emissions, dialogic fragments, semantic continuities
• Image-based content, camera-captured constructs, gallery-sourced visual artifacts
• Voice recordings in raw waveform, compressed formats, or derivative spectrographic encodings
• Paralinguistic byproducts including tone, cadence, and vocally inferable emotional vectors

1.2 Device-Generated Telemetric Residua

• Hardware model identifiers, OS distribution parameters, device architecture fingerprints
• Network ingress metadata including IP vectors, geospatial approximations, temporal stamps
• Application usage chronologies, interaction cadences, and system-triggered behavioral logs

1.3 Environmental Permission-Conditioned Data

• Microphone-captured auditory segments
• Camera-captured visual frames
• User-granted locational coordinates (coarse or precise)
• Notification channel tokens, foreground/background state transitions

1.4 Algorithmically Synthesized or Inferred Constructs

• Speech-to-Text (STT) transcripts
• Derived emotional landscapes inferred through computational heuristics
• Latent conversational embeddings utilized by the Application’s large language model (LLM)
• Predictive engagement vectors and personalization matrices

2. Epistemic Utilization & Multi-Level Computational Processing

User-originating and system-inferred constructs may undergo complex processing pipelines:

2.1 Linguistic Transmutation & Dialogue Fabrication

Inputs may be subjected to:

• Semantic interpretation via self-hosted LLMs
• Generative synthesis yielding contextualized responses
• Integration into session-persistence memory schemas
• Behavioral modeling aimed at replicating emotional authenticity

2.2 Vocophonic Synthesis (TTS Pipeline)

The Application may propagate generated text through:

"Supplementary computational agents operating within autonomous extrinsic infrastructures, deputized to execute the parametric reconstitution of linguistic output into perceptible vocophonic auralities."

In essence: internally hosted TTS engines convert text → voice.

2.3 Auditory Transcription (STT Pipeline)

User-submitted voice may be analyzed to produce:

• Textual representations
• Contextual markers
• Auxiliary semantic clues

2.4 Telemetric Optimization & Experiential Calibration

The Application may utilize data for:

• Latency minimization
• Feature-tuning
• Behavioral anomaly detection
• Session continuity stabilization
• Internal model enhancement

3. Interoperability With Computational Superstructures

3.1 Self-Hosted Engine Matrix

The Application integrates:

• Self-hosted LLM instances on GPU-backed compute nodes
• Proprietary TTS/STT engines running on Azure cloud infrastructures
• n8n-orchestrated workflow automations
• Postgres-backed persistence layers
• Internal logging superstructures

3.2 Platform-Imposed Architectural Dependencies

Infrastructure providers such as:

• Firebase (authentication, storage constructs)
• Azure Virtual Machines (GPU-enabled inference nodes)
• PostgreSQL Clusters (relational persistence)
• Containerized service meshes

may transiently process or route user-derived constructs solely as required for operational viability.

4. Retention, Durational Logic & Terminal Dissolution

4.1 Retention Durations

• Textual conversations → retained until explicit user deletion
• Voice recordings → retained for feature continuity, diagnostics, and session stability
• Images → retained while contextually required
• STT transcripts → retained transiently during session flow
• LLM contextual embeddings → ephemerally stored
• Logs → retained per infrastructural defaults

4.2 Mechanisms of Dissolution

Upon account deletion:

• Conversational archives undergo irrevocable excision
• Voice files, images, STT artifacts → purged
• Persistent identifiers → nullified
• Secondary logs → dissolved based on platform constraints
• Infrastructure-level cached constructs → invalidated as feasible

5. Systemic Safeguards & Risk Postulates

The Application relies upon:

• Access-controlled computational partitions
• Compartmentalized data-handling topologies
• Restricted inter-service pipelines
• Hosting-enforced integrity constraints

No assertion of cryptographic absoluteness, imperviousness, or unconditional invulnerability is made. Technological engagement entails residual risk.

6. Minor-Inclusion Prohibition

The Application is not intended for individuals under 13. Incidental access triggers immediate artifact dissolution.

7. User Privileges & Juridical Autonomies

Users may exercise rights to:

• Access their stored constructs
• Rectify inaccuracies
• Initiate deletion
• Withdraw engagement

Identity verification may be mandated.

8. Amendment, Reinterpretation & Temporal Evolution

This Codex may be:

• Expanded
• Redefined
• Recalibrated
• Recontextualized

Your continued use constitutes implicit assent.

9. Contact Nexus

For juridical, administrative, or interpretive correspondence: