Data Engineering
ETL pipelines, data validation, schema contracts, dataset versioning, registry systems, PostgreSQL workflows, and structured exports.
Data Engineering · AI Systems · Infrastructure
Modern Engineering
for Data-Driven Systems.
iniData designs and deploys robust data pipelines, backend systems, automation platforms, AI workflows, and infrastructure foundations for teams that need reliable software instead of fragile prototypes.
What iniData builds
Systems that connect data, software, and infrastructure.
From ingestion pipelines to Docker deployments and analytical web applications, iniData focuses on complete systems that can be maintained, extended, monitored, and trusted.
Backend Platforms
Python services, FastAPI systems, REST APIs, background jobs, orchestration logic, CLI tools, and modular service architecture.
AI & Statistical Systems
Machine-learning pipelines, simulation tools, evaluation workflows, feature engineering, model comparison, and practical AI automation.
Infrastructure & Deployment
Dockerized applications, Linux server operations, Traefik reverse proxies, HTTPS automation, cron jobs, and production deployments.
Security & Networking
Secure server access, SSH infrastructure, reverse proxy routing, authentication concepts, network analysis, and reliability-oriented design.
Web & Mobile Systems
Responsive static websites, interactive dashboards, iOS application architecture, encrypted local storage concepts, and user-facing tooling.
Featured Project
LottoQuant
LottoQuant is a quantitative lottery analytics platform for Swiss Lotto and EuroMillions. It combines automated data collection, historical jackpot analysis, expected-value calculations, Monte Carlo simulations, bankroll scenarios, and a professional web dashboard.
Approach
Engineering discipline before complexity.
iniData prioritizes clear architecture, small reliable components, explicit data contracts, reproducible deployments, and observable workflows. The goal is not to add technology for its own sake, but to build systems that remain understandable under real-world pressure.
This means clean interfaces, validation at boundaries, meaningful logs, automated updates where useful, and deployments that can be explained, rebuilt, and extended.
Need a reliable technical system?
iniData can help with data pipelines, backend systems, automation workflows, infrastructure modernization, dashboards, and AI-powered tooling.
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