Building Haqikos: Architecture of a Next-Gen AI Startup

When starting Haqikos, our core philosophy was speed of iteration without sacrificing reliability. We needed a stack that allowed us to rapidly prototype AI features while handling production-scale data streams.

The Core Technical Stack

We settled on a modern, battle-tested ecosystem:

• Frontend: Next.js 14 with App Router, deployed on Vercel for instant edge-caching and serverless execution.
• Backend & Database: Prisma ORM with PostgreSQL (hosted on Neon) for a serverless, scalable data layer.
• AI Orchestration: Custom Python microservices utilizing LangChain and FastAPI to handle heavy LLM inferences.

Why Not a Monolith?

While a monolith is great for MVP, AI workloads require specific hardware. Our Node.js frontend needed to remain lightweight and responsive, while our AI processing required GPU clusters and long-running background tasks. By decoupling the AI logic into asynchronous Python workers, our UI never blocks.

Building a startup is 10% coding and 90% iterating based on user feedback. The Haqikos architecture is designed exactly for that: resilient, scalable, and built for speed.