How I Built Speakify in 3 Weeks

Building a SaaS product from scratch and shipping it in under a month sounds crazy. But that's exactly what happened with Speakify — a text-to-speech platform that now supports 300+ voices across 50+ languages.

Here's how it went down.

What is Speakify?

Speakify is an AI-powered text-to-speech SaaS. You paste in text, pick a voice and language, and get natural-sounding audio back. It's built for content creators, educators, and developers who need high-quality TTS without the complexity of raw APIs.

Try it yourself: speakify.eu.org

The Tech Stack

I went with a split architecture:

• Frontend: Next.js with Tailwind CSS — fast to build, great DX
• Backend API: FastAPI (Python) — handles the heavy lifting of TTS processing
• Database: PostgreSQL via Neon — serverless, scales to zero
• Deployment: Vercel for frontend, VPS for the FastAPI backend

Why FastAPI for the backend?

The TTS processing is CPU-intensive. Python has the best ecosystem for AI/ML tasks, and FastAPI gives you async support out of the box. The type hints + automatic OpenAPI docs are a massive productivity boost.

The Build Timeline

Week 1: Core Engine

The first week was all about getting the TTS pipeline working. I integrated multiple TTS providers to offer variety in voices. The key insight was abstracting the provider layer — each TTS service implements the same interface, so adding new providers is trivial.

class TTSProvider:
    async def synthesize(self, text: str, voice: str) -> bytes:
        raise NotImplementedError

Week 2: Frontend + API

Week two was building the user-facing product. Next.js made this fast. The main challenges were:

1. Audio streaming — sending audio back to the client efficiently
2. Voice browser — making 300+ voices searchable and filterable
3. Rate limiting — preventing abuse without hurting UX

Week 3: Polish + Launch

The final week was all about:

• Error handling and edge cases
• Loading states and feedback
• SEO and meta tags
• Writing docs
• Setting up monitoring

Lessons Learned

1. Ship the MVP, then iterate

I launched with 50 voices. The remaining 250+ came in updates over the following weeks. If I'd waited for "complete," I'd still be building.

2. Abstractions pay off early

The provider abstraction I built in week 1 saved me dozens of hours later. When I added a new TTS provider, it took 30 minutes instead of 3 days.