Somiqora

#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

• 1.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.
• 2.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.
• 3.Separated the transcription service, OpenAI orchestration, and file delivery into distinct Nest.js service layers — each independently testable and replaceable.
• 4.Used Next.js SSR for public-facing discovery pages and client-rendered React for the voiceover editor, balancing SEO with interactive performance.