We pick production-hardened, maintainable tools designed for speed, scale, and long-term codebase health.
Use the buttons below to filter the technologies we actively use in client engagements.
We pick technology stacks based on performance, developer speed, and hosting efficiency. Here is our technical rationale.
Next.js implements server-side generation (SSG) and incremental static regeneration (ISR). This means pages are compiled into static assets and cached at CDN edge nodes globally. Users experience page loads in under 200ms, and search crawlers index fully populated semantic HTML, maximizing SEO positioning. Additionally, the component-driven structure of React allows creating highly reusable, type-safe frontend UI kits.
Python FastAPI is one of the fastest backend frameworks because it runs on top of Starlette and Uvicorn asynchronous servers. It automatically parses query payloads into typed Pydantic structures and generates live Swagger interactive documentation. For AI workloads, Python is the native programming language, meaning LangChain, vector DB clients, and model APIs integrate with zero library mismatch issues.
PostgreSQL is a mature, production-grade relational database engine that supports transactional consistency (ACID rules), JSON schema fields, and complex indexing mechanisms. Using PGVector, it handles semantic vector embedding searches alongside traditional user tables, eliminating the need to sync data between a main database and a separate vector database. When connected to Supabase, it supports Row-Level Security (RLS) policies directly at the database engine level.
