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Computer Vision · Point Clouds · Geospatial · WebGIS · LLM/RAG · MLOps · Switzerland

Vahid Aghajani

I build at the intersection of geospatial, WebGIS and computer vision — photogrammetry, point clouds, imagery ML, the map front-ends and the system design behind them — now with LLM, RAG and MLOps pipelines layered on top. Eight-plus years turning raw spatial and document data into shipped systems, end to end from data to model to API to map to deploy. Based in Switzerland.

About

I like building end-to-end: from the model that makes the decision, to the API serving it, to the server it runs on. A system isn't finished when the code compiles — it's finished when it's deployed, monitored, and quietly doing its job.

My background sits at the intersection of geospatial, WebGIS and computer vision — photogrammetry, point clouds and LiDAR, object detection and segmentation on aerial, satellite and industrial imagery, the map front-ends (OpenLayers/MapLibre) and the backend system design to run them — with modern LLM, RAG and MLOps work layered on top.

I started this blog to teach younger software engineers the things I wish someone had told me at the beginning of my career — the practical notes on LLMs, RAG, computer vision and shipping AI that I had to learn the hard way.

Tech Stack

Programming Languages

PythonC++JavaScriptTypeScript

Frameworks & Web

FastAPIFlaskReactViteMicroservicesROS2

AI / ML & Computer Vision

PyTorchYOLOOpenCVDetectron2Open3DLLM IntegrationRAG / pgvector

Databases

PostgreSQLPostGISRedisSQLAlchemy

Servers, DevOps & Deployment

DockerDocker ComposeLinux (Ubuntu)NginxGunicornCeleryPrometheus / GrafanaCI/CD (GitHub Actions)HetznerAWSGoogle Cloud

Specialized Domains

GISADASPhotogrammetryPoint CloudsVisual OdometryThree.js

Areas of Expertise

Geospatial & Computer Vision

  • 3D point cloud classification & segmentation at scale
  • Object detection for infrastructure and photogrammetry pipelines
  • WebGIS front-ends (OpenLayers, MapLibre) over PostGIS pipelines

LLM Integrations, RAG & AI Agents

  • RAG document Q&A with vector search and source grounding
  • Agentic workflows with tool use and function calling
  • LLM orchestration across OpenAI, Anthropic, and open-source models
  • Production ML infrastructure — containerized, monitored, retrainable

Scalable Web Architectures

  • Full-stack React + FastAPI / Flask platforms
  • Auth, payments, email, analytics — end-to-end delivery
  • 5+ platforms currently running in production

Servers, DevOps & Deployment

  • Linux server setup from bare VPS — Docker Compose, Nginx, SSL, backups
  • CI/CD pipelines and automated deploys via GitHub Actions
  • Celery workers, cron jobs, Gunicorn — background processing and scheduling
  • Monitoring and alerting with Prometheus, Grafana, cAdvisor, node-exporter
  • Operating a fleet of production servers on Hetzner, AWS, and GCP
YouTube

Teaching: AI Engineering from Scratch

Build AI applications from scratch in Python — one free, hands-on episode at a time.

Open source

Open-Source Projects

Production-shaped code you can clone, read, and run — the same patterns I write about.

Working together

I take on freelance work in exactly the areas above — computer vision and point clouds, geospatial and WebGIS, LLM/RAG pipelines, and the system design to run them in production. Discovery sprints, consulting, or a project delivered end to end.

See how that works →

Let's Connect

I enjoy talking shop with other engineers and researchers — LLM integration patterns, 3D perception pipelines, or just swapping notes on shipping things to production. Always open to a technical exchange.