DevN — Software and Artificial Intelligence Mastery
data, software, and infrastructure at scale.
DevN is an independent software engineering and artificial intelligence studio led by Neilos Psathas. We design, build, optimize, and deploy software systems from machine learning pipelines and backend infrastructure to complete web and mobile platforms.
We work where complex data, intelligent algorithms, and reliable software architecture meet. We focus on turning demanding technical problems into maintainable, efficient, scalable production-oriented solutions.
Python / TypeScript / Machine Learning / System Architecture
Reference architecture
01 / The Core
Good engineering connects the entire system. From model inference and data pipelines to application architecture and infrastructure, We build solutions with the complete lifecycle in mind.
We develop machine learning systems focused on practical problems, including anomaly detection, pattern recognition, analytical automation, and decision support. Our work covers data preparation, model evaluation, optimization, and the integration of intelligence into real applications.
Python / scikit-learn / PyTorch / TensorFlow / Elasticsearch
We engineer complete software platforms with particular strength in backend systems, API design, data layers, and integrations. We care about maintainable architecture, clean interfaces, dependable behavior, and cost-efficient implementation.
Python / TypeScript / Node.js / Django / FastAPI / React / SQL
A machine learning model creates real value when it can operate reliably inside a system. We work on model serving, inference optimization, deployment workflows, monitoring, and the integration of AI capabilities into production software.
Python / Docker / Kubernetes / AWS / REST APIs / Model Serving
We design ETL processes, data integrations, transformation pipelines, and analytical workflows that convert heterogeneous sources into consistent, clean, actionable and useful datasets.
Python / polars / pandas / SQL / NoSQL / Elasticsearch / APIs / ETL
We examine bottlenecks, unnecessary complexity, inefficient computation, and operational overhead. We focus on performance optimization, sensible architecture, observability, and balancing technical requirements with infrastructure cost.
Profiling / Caching / Docker / Grafana / Prometheus / Optimization
We design and develop web and mobile applications, connecting practical user experiences with reliable backend services, data processing, algorithms, and external systems.
React / Android / iOS / Flutter / REST APIs / Node.js
02 / Selected work
Our work spans from fraud prevention, machine learning, logistics, data engineering, mobile applications, intelligent infrastructure to developer tooling. Here is a selection of the systems and products we have contributed to or developed.
03 / Engineering lab
Some ideas begin as client requirements. Others begin as experiments, performance questions, or a better way to structure code. The engineering lab brings together open-source work, prototypes, and explorations in software architecture and intelligent systems.
Software architecture / developer tooling
An open-source agent skill for multi-tenant, role-scoped, auditable full-stack CRUD applications: a generic CRUD factory, shared browser/server business rules, and clean controller hooks.
View repositoryAnomaly detection · LLM integration
Anomaly detection, analytical automation, LLM integration, and practical machine learning.
Related: CALLIRRHOE AI demoPatterns · multi-tenancy · maintainability
Reusable patterns, backend design, multi-tenant systems, and maintainable application structures.
DevN-gr on GitHubProfiling · inference optimization
Inference optimization, profiling, efficient data processing, and reducing unnecessary software complexity.
Browser technologies · visualization
Experimenting with browser technologies, programmable visualizations, and interfaces that make complex systems understandable. Move your pointer across the drawing.
04 / The engineer
I'm Neilos Psathas, a software engineer and data scientist based in Greece, and the person behind DevN.
Over more than a decade, I've worked across software development, machine learning, backend systems, data engineering, mobile applications, and the infrastructure that supports them.
My work has involved everything from experimental AI applications and public transportation data systems to logistics platforms and fraud detection technologies.
I'm especially interested in problems that sit between disciplines: where data science depends on good software engineering, where application performance affects operating cost, and where complex backend systems need to deliver simple, reliable experiences.
My preferred approach is pragmatic. Understand the problem, design the smallest architecture that solves it well, measure what matters, and improve where evidence shows it is necessary.
04 / The engineer — education
Studied Electrical and Computer Engineering at the University of Thessaly, with additional education in software engineering, data science, and applied machine learning.
05 / The beginning
Whether you're exploring an AI-powered product, modernizing an existing application, optimizing an an old system, or building something entirely new, We can help turn the technical challenge into a practical solution.
Available for selected software engineering, data science, AI, and technical consulting engagements.