Streaming AI Coach
A WebSocket and REST-based chat interface delivers streaming responses, media attachments, pagination, date separation, retry behavior, and a high-performance virtualized conversation interface.

A personalized AI mental health app focused on everyday mental wellness, combining streaming AI conversations, guided journaling, personalized meditations, offline access, behavioral engagement analytics, and optional SMS-based companionship within a cross-platform mobile experience.

The application is an AI companion app that combines conversational AI, structured wellness activities, journaling, personalized audio meditation, and persona-driven coaching. Users receive streaming responses from a digital companion while accessing journals and downloaded meditations even when offline. The platform also includes an optional SMS companion, multilingual support, authentication, analytics, attribution, feature flagging, and push notifications. Its mobile architecture balances personalization and continuous engagement with secure credential handling, privacy controls, reliable state management, and cross-platform deployment.
Sensitive Firebase configuration, analytics credentials, mobile tokens, and native configuration files could not be committed to source control, complicating automated development, onboarding, testing, and deployment.
The mobile experience required secure build automation, native-module support, iOS privacy compliance, over-the-air updates, and fast iteration without exposing production credentials.
Streaming conversations, offline journals, cached media, API data, authentication, feature flags, analytics, and multiple app routes required clear separation between persistent client and server state.
Ditstek implemented a secure cross-platform architecture combining Expo EAS, typed APIs, offline caching, streaming communication, privacy-aware analytics, native mobile integrations, and structured state management for continuous wellness experiences.
Production credentials are injected through EAS secrets and build profiles, allowing automated CI, TestFlight, and App Store workflows without committing sensitive configuration to source control.
Expo and a custom development client support native Firebase and CleverTap capabilities alongside OTA releases, accelerating iteration without sacrificing required native integrations.
Zustand and MMKV manage persistent client state while TanStack React Query handles remote server state, caching, synchronization, and request lifecycle responsibilities.
OpenAPI-generated clients provide a shared contract between mobile and backend services, reducing implementation drift and creating more predictable integration across evolving API versions.
Adjust attribution initializes only after App Tracking Transparency permission, while PostHog and CleverTap support feature analysis, engagement events, user profiles, and notifications.
Cached journal sessions and meditation audio remain available without connectivity, strengthening the digital wellness platform experience whenever network conditions interrupt normal API access.
The AI coaching platform brings together conversational support, persona-based onboarding, guided reflection, generated meditation, offline-first access, analytics, multilingual experiences, and secure authentication within a unified mobile wellness environment.
A WebSocket and REST-based chat interface delivers streaming responses, media attachments, pagination, date separation, retry behavior, and a high-performance virtualized conversation interface.
Resumable onboarding captures structured responses through multiple-choice questions, sliders, and scales before assigning users one of five configurable AI coaching personas.
The guided meditation app experience provides generated sessions with play, pause, seek, autoplay, eligibility checks, and cached offline audio through a dedicated media service.
Journal entries integrate with conversational sessions and support guided templates, draft autosaving, publishing, deletion, and offline access through locally persisted application state.
Recent journals and meditation content appear within a combined dashboard offering quick actions, meditation generation entry points, and companion-subscription management.
An optional text-based companion uses phone verification and subscription controls to extend conversational wellness support beyond the primary mobile application.
PostHog, CleverTap, and Adjust provide product analytics, session replay, configurable feature releases, engagement tracking, push notifications, and mobile marketing attribution.
Apple, Google, Magic Link, token refresh, Terms handling, suspended-user routing, and deferred deep links create resilient authentication and navigation experiences.
English, French, and Spanish localization combines with centralized theme tokens, responsive breakpoints, animations, gesture handling, and structured routing across multiple application screens.
Streaming conversations and offline wellness content give users access to core coaching, journaling, and meditation experiences across changing connectivity conditions.
Persona assignment, onboarding responses, meditation generation, journals, and behavioral analytics create a personalized coaching app experience shaped around individual interaction patterns.
Local caching allows journals and downloaded meditations to remain accessible even when API requests cannot be completed because the device is offline.
Expo EAS, typed APIs, OTA capabilities, and automated deployment workflows provide developers with a more controlled approach to releasing and maintaining functionality.
Feature flags, analytics, push notifications, attribution tracking, activities, and an optional SMS companion create multiple mechanisms for supporting sustained user engagement.
The architecture provides a reusable mobile foundation for conversational coaching, personalized content, multilingual delivery, media experiences, authentication, analytics, and future feature expansion.