Affordable software tools for professional problem-solvers

Quadyne builds focused tools that help engineers, analysts, and consultants do deep work faster — without enterprise price tags, lock-in, or bloat.

Why Quadyne

You may already have spreadsheets, generic BI tools, and big-name software. Quadyne fills the gap between one-off scripts and bloated platforms.

Built around real workflows

Every product starts from real client work — planning studies, audits, and reports we’ve had to deliver ourselves.

Affordable & transparent pricing

No surprise “per-seat” upcharges. Simple pricing that makes sense for small teams and independent professionals.

Own your data

Keep your files in your own environment. Export whenever you want. No lock-in, no dark patterns.

Optimized for speed

Load large datasets smoothly, generate charts quickly, and spend more time on engineering judgment than on wrangling tools.

Opinionated, not bloated

We say “no” to features that slow you down. Each product is deliberately narrow and deep.

Backed by engineering expertise

Quadyne is built by engineers experienced in power systems, electronics, software, and optimization — not generic app factories.

Resources

  • PID in Python: Speed Control of a Real DC Motor

    We designed a speed controller for a real motor, the ABB Baldor-Reliance CDP3306 (¼ HP, 180 V, 1750 rpm), using only Python and its datasheet. The result settles a 1000 rpm step in 75 ms with no overshoot, a 76° phase margin, and a peak demand of 117 V from a 180 V drive. Everything…

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  • PID Control, Demystified

    A PID controller acts on three views of the same error: its size now (P), its history (I) and its rate of change (D). Getting the gains right is only half the job. Real hardware adds actuator limits, sensor noise and sampling, and each one breaks the textbook law in a predictable way. This post…

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  • Model-Based Controller Development: From Requirements to Real Hardware

    Model-based development takes a controller from requirements to real hardware in eight stages, and it catches most problems before any hardware is at risk. You design against a model of the system, then verify the same design again at every step as it turns into code and runs on real electronics. This post walks through…

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