From data to ML — simply, locally.

DataWizardML is an early-stage, local/on-prem tool that turns raw datasets into reproducible machine-learning pipelines. No hosted service — your data stays where it lives.

Illustration: simple data → ML pipeline (local)
Runs on your machine or server — no cloud transfer.

Overview

Connect to your datasets, check structure and quality, then build a repeatable pipeline: ingest → profile → prepare → train → deploy. The emphasis is clarity over complexity and keeping everything under your control.

Planned capabilities

Design approach

No cloud dependency. Installation is meant for desktops or private servers (including isolated networks). This suits teams with sensitive data or regulatory constraints who prefer full local control.

Goals

Frequently Asked Questions

Is this cloud-based?
No. DataWizardML is intended to run on local machines or private servers. Your datasets stay in your environment.
Who is this for?
People and teams who want a clear, repeatable path from raw data to useful models without sending data to external services.
What does “local deployment” mean?
After training, results can be packaged into a small service or scheduled job that runs on your own machine or server.
Do I need internet?
Not for day-to-day use. Internet is only helpful for updates or documentation if you choose.
When will it be available?
We’re exploring interest and gathering feedback. If you’d like to try an early version, leave a note in the contact form.
Will this replace my current tools?
It’s meant to complement what you have by simplifying repetitive steps and creating a consistent pipeline you can run locally.

Contact

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