Somiqora
AI Text-to-Speech platform for natural voiceovers
#problem
Somiqora is an AI-driven text-to-speech platform that turns written content into natural, human-like voiceovers. It addresses the gap between raw text and production-ready audio, giving content creators a way to generate spoken output without manual recording or editing. The platform combines OpenAI for language understanding with Amazon Transcribe for speech-to-text workflows behind a Next.js interface.
#what-i-built
I architected the platform end to end, owning the Nest.js backend, the Next.js frontend, and the integration layer between them.
I built the Nest.js backend services that orchestrate text processing and voiceover generation requests.
I integrated OpenAI into the backend to handle natural language processing for the text-to-speech pipeline.
I wired in Amazon Transcribe to support speech-to-text workflows within the platform.
I developed the Next.js web client through which users submit text and retrieve generated voiceovers.
#stack
#outcome
Production AI text-to-speech platform live at somiqora.com: end-to-end ownership across Nest.js backend, Next.js frontend, OpenAI NLP integration, and Amazon Transcribe speech workflows.
#key-decisions
Combined OpenAI for language understanding with Amazon Transcribe for speech processing rather than a single provider, using the best-fit model for each pipeline step.
Designed voiceover generation as an async queue-based flow so long audio jobs do not block the UI: users receive progressive feedback rather than waiting on a synchronous request.
Separated the transcription service, OpenAI orchestration, and file delivery into distinct Nest.js service layers: each independently testable and replaceable.
Used Next.js SSR for public-facing discovery pages and client-rendered React for the voiceover editor, balancing SEO with interactive performance.
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