The product challenge
A learning MVP needed to work across mobile platforms while connecting conversational, speech-to-text and semantic-analysis capabilities through a coherent user flow.
CASE STUDY / REACT NATIVE & AI
AI became part of a usable learning workflow.
The project connected a cross-platform product experience with practical language and voice services instead of treating AI as a separate demonstration.
First-hand engineering experience · verified project outcomes
The application layer
React Native, Expo and type-safe frontend patterns supported a shared cross-platform experience and kept product iteration focused on the learner workflow.
The AI service layer
Python services integrated ChatGPT for conversational capabilities, Whisper for speech-to-text and Sentence-BERT for semantic search and voice-analysis tasks.
The engineering outcome
The result was an end-to-end MVP architecture spanning the client experience and AI-backed services. Private product data, prompts and internal service contracts are intentionally omitted.
The reusable lesson
AI features become product capabilities only when latency, failure states, data flow and the surrounding interface are designed as one system.