Inward

A voice-first journaling and CBT-reframing companion that is verifiably airplane-mode functional — spoken thoughts are transcribed, reflected, and stored only on the phone.

Concept

A voice-first journaling and CBT-reframing companion that is verifiably airplane-mode functional — spoken thoughts are transcribed, reflected, and stored only on the phone.

Edge AI

• On-device Whisper-class ASR for voice entries
• AFM 3 Core with Dynamic Profiles running listener
• CBT-reframe (cognitive distortions via @Generable structured output), and weekly-review modes
• Spotlight local RAG retrieves past entries for longitudinal patterns
• a LoRA adapter trained on reflective-questioning style as an uncopyable differentiator.
• Android: Gemini Nano Summarization/Rewriting/Prompt APIs on flagships, Gemma 3n E2B via LiteRT-LM elsewhere.

Tech Stack

• iOS (primary, iOS 26.4+): Swift/SwiftUI
• SpeechAnalyzer + SpeechTranscriber for on-device ASR (whisper.cpp small as fallback for older devices)
• FoundationModels AFM 3 Core via LanguageModelSession with @Generable structured output for distortion-tagging and reflection prompts, using the new context-size/token-count APIs to chunk under the 8K window with hierarchical entry summaries
• Core Spotlight + NLContextualEmbedding (or a small Core ML embedding model) + sqlite-vec for local RAG over past entries; GRDB/SwiftData with SQLCipher and NSFileProtectionComplete; skip the custom LoRA adapter at launch (version-lock retraining tax) in favor of a prompt-engineered persona with few-shot exemplars; client-side-encrypted export to Files/iCloud Drive. Android (downscoped, flagships first): Kotlin/Jetpack Compose
• ML Kit GenAI Summarization + Rewriting APIs on the AICore-supported device list, Prompt API only for short single-entry reflections (respect 4K-in/255-out limits); Gemma 3n E2B-it int4 via LiteRT-LM / MediaPipe LLM Inference as an opt-in download for non-AICore devices; on-device SpeechRecognizer or whisper.cpp for ASR
• Room + SQLCipher
• EmbeddingGemma-class embeddings via LiteRT + sqlite-vec for local retrieval. Both platforms: no analytics SDKs, no network calls in the journaling path (verifiable via iOS App Privacy Report)