01Industrial AI platform
SWAPP
An AI-first industrial data workbench that brings signal exploration, trends, statistics, PPM views, governed APIs, and natural-language workflows into one product.
AI practitioner · Industrial systems
Industrial intelligence,
built for the real world.
I'm Serdar Gündoğdu—an engineer and AI practitioner who turns complex industrial data into usable products, dependable machine learning systems, and faster decisions.
Based in TürkiyeWorking globally
From raw plant data
to governed intelligence
to decisions people can trust
Selected work
Products, systems, and tools that move beyond the demo.
A selection of industrial platforms and open-source tools shaped around real workflows—not isolated models.
02Open-source Python package
PIPolars
A high-throughput bridge from the PI System to Polars DataFrames—designed for bulk extraction, lazy evaluation, and practical caching in industrial analytics workflows.
03Adaptive learning system
AI Practitioner Dev OS
A project-based operating system for becoming a stronger AI practitioner, with a 12-month adaptive curriculum and agents for planning, building, reviewing, and evaluation.
How I work
Engineering discipline. AI-native pace.
I combine industrial context, statistical thinking, and modern AI development workflows to close the gap between an idea and a system people can actually use.
Frame the decision
Start with the operator, engineer, or business decision—not the model. Define the signal, constraint, and useful action.
Build the full loop
Connect data, analysis, APIs, interface, and feedback so the intelligence survives outside a notebook.
Make it operable
Design for traceability, human review, deployment constraints, and the realities of industrial environments.
Predictive analyticsTime seriesIndustrial data platformsApplied machine learningAI-assisted software delivery
Open lab
Tools for learning by doing.
Packages, platforms, and interactive experiments that make difficult concepts easier to explore.
01
.NET package
PIWebAPI
A REST layer for PI Points, AF hierarchies, StreamSets, and Event Frames.
02Industrial platform
SCADA Nerve
A focused platform for SCADA monitoring, automation, and operational visibility.
03Learning platform
Industry-Learn
Applied machine-learning patterns and workflows grounded in industrial problems.
04Interactive lab
Scikit-Play
A hands-on playground for understanding and comparing classical ML algorithms.
05Time-series lab
Aeon-Play
Interactive experiments for time-series analysis and forecasting with Aeon.
06Deep-learning lab
PyTorch-Play
A visual environment for experimenting with neural networks and model behavior.
07Learning platform
DSML101
Clear, practical resources for building a foundation in data science and ML.
About
I sit at the intersection of engineering, data, and product delivery.
My background spans statistics, mathematics, mechanical and industrial engineering. That mix helps me see AI as a complete operating system: the data foundation, the model, the interface, the deployment path, and the people making the final decision.
I use AI coding partners such as Codex, Claude Code, and Gemini as part of a disciplined development workflow—accelerating research and implementation while keeping architecture, validation, and accountability human-led.
Have an industrial AI problem worth solving?
Let's build something useful.