07 / 08·Brand · Product · Build·Live
Summaraize
Speech-to-text, document conversion, summarization, and text-to-speech with credits.
§ 01·The brief
Fig. A — Problem · Position · Constraint
What it solves.
Summaraize is a Next.js application that turns messy, time-consuming inputs (meeting audio, lecture recordings, PDFs, scanned images, long documents) into structured outputs: transcripts, summaries, and natural-sounding audio. It supports voice and document workflows and enforces a credit-based usage model with cost estimation and deduction at API boundaries.
- Manual transcription is slow and error-prone
- Information overload in long documents
- Paper/scanned content is hard to search
- Accessibility and learning preferences via text-to-speech
- Unpredictable cost and abuse risk in AI apps via credits
Speech-to-text, document conversion, summarization, and text-to-speech with credits.CASE 07 · Field log
§ 02·Design
Fig. C — Surfaces, type, motion
What's in the box.
- 01Voice Assistant: record/upload audio → transcribe → summarize → generate AI voice
- 02Document Converter: PDF/image/text → extract (including OCR) → summarize → generate AI voice
- 03Provider fallback for summarization (DeepSeek → OpenAI)
- 04Credit estimation and enforcement at API boundaries
- 05Stripe checkout + webhooks for credits/subscriptions
- 06SEO blog with Open Graph, JSON-LD, and sitemap generation
- 07Analytics integrations gated behind cookie consent where applicable
§ 03·Build
Fig. D — Architecture, shipped
Typed end to end.
- 01Next.js (App Router) + React + TypeScript
- 02Tailwind CSS + shadcn/ui (Radix UI primitives)
- 03Supabase (Auth, Postgres, Storage)
- 04Stripe (Checkout + Webhooks)
- 05Deepgram (speech-to-text)
- 06DeepSeek + OpenAI (summarization + extraction)
- 07Google Cloud Text-to-Speech