Cortex AI
Any visitor can query my professional background, stack and project decisions in natural language. No page-scanning required.
The Problem:
A traditional portfolio is a passive document. Recruiters and potential clients spend seconds scanning it — and leave without grasping the depth of the work. VazquezDev needed a way to turn passive visitors into active conversations: answering specific questions on demand without forcing anyone to read page by page.
- Static pages can't answer "what's your RAG stack?" or "have you done this before?"
- VazquezDev's work spans too many dimensions to fit in a simple scroll
- Most portfolio visitors leave with an incomplete picture
Objective:
Turn vazquezdev.pro into an interactive layer where anyone can query the full professional profile — experience, projects, stack, and services — in a single natural-language flow:
- One entry point for everything: experience, projects, stack, services
- Multilingual from day one
- Fast, low-latency answers — no waiting
Stack & highlights:
- Frontend: Vue 3 · Vite
- Backend: FastAPI · Python
- Vectors: ChromaDB — lightweight self-hosted storage
- LLM: Groq API — ultra-low latency, near-zero inference cost
- Ops: Docker · Traefik · VPS
- Fully decoupled frontend and backend
- Knowledge base built from professional history and real projects
- Conversational access to the full professional context behind this portfolio
Outcome:
vazquezdev.pro now behaves like a conversational assistant over curated professional context:
- Self-hosted vector layer — portfolio knowledge stays server-side
- Ultra-low latency inference through Groq
- Each layer of the stack evolves independently




