How I Built Speakify in 3 Weeks
A deep dive into building a TTS SaaS with 300+ voices and 50+ languages — from idea to launch.
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:
- Audio streaming — sending audio back to the client efficiently
- Voice browser — making 300+ voices searchable and filterable
- 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.
3. Serverless isn't always the answer
For the API server, a persistent VPS was the right call. TTS processing needs consistent CPU, and cold starts would kill the user experience.
4. Build in public
Sharing progress on social media brought early users, feedback, and motivation. The accountability of public building is real.
What's Next?
Speakify is growing. On the roadmap:
- API access for developers
- Batch processing for long documents
- Custom voice cloning (experimental)
- Chrome extension for quick TTS
If you're thinking about building a SaaS — just start. Pick a problem, pick your stack, and ship something in 3 weeks. You'll learn more from shipping than from planning.
Arbind Kumar is a developer, educator, and SaaS builder from Assam, India. Follow the journey at ArbindBuilds.
