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FastTrackML

Free#28 of 38 in ML Experiment Tracking Software

FastTrackML: A focused, open-source MLflow-compatible server for self-hosted run tracking. Ranked #28 of 38 in ML Experiment Tracking Software by our editors (6.1/10); pricing: Open source; best for users wanting a simple self-hosted MLflow-compatible server.

6.1/10Editor score

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FastTrackML6.1 Visit FastTrackML

At a glance

Editor score
6.1 / 10
Pricing
Open source
Best for
Users wanting a simple self-hosted MLflow-compatible server
Paid from
Free
Facts checked
21 Sep 2026

Where it wins
- Logs run parameters and metrics through an API
- Web, MLflow, and Aim UIs visualize experiment results
- Pip and Docker deployment support self-hosted setups
Where it doesn't
- Self-hosted deployment requires your team to operate the server
- Community support is the listed support channel
- Archived repository and successor status raise continuity concerns

Our verdict on FastTrackML

FastTrackML was an open-source machine-learning experiment tracking server from G-Research. It was designed for teams that wanted to log run parameters and metrics through an API, then inspect experiment results in a web interface. Its self-hosted model can fit small, mid-market, and enterprise teams that prefer to operate their own tracking service rather than adopt a hosted product.

The product’s main ecosystem advantage is MLflow compatibility. It provided tracking-server behavior intended as a drop-in replacement for the MLflow tracking server and included both MLflow and Aim visualization UIs. Teams could install it with pip, shell or PowerShell scripts, or Docker, while the published platform coverage included web, Windows, macOS, Linux, API, and self-hosted deployment. That combination suits workflows already organized around MLflow-compatible clients or teams that want multiple visualization interfaces without changing their tracking model.

The trade-off is operational ownership and project continuity. A self-hosted deployment places installation, upgrades, availability, and maintenance with the adopting team, and community support is the listed support channel. The official website identifies mlflow-go as FastTrackML’s successor, while the G-Research repository was archived on March 31, 2026. Buyers seeking a simple server for an existing MLflow-oriented workflow may still find the feature set appropriate, but teams prioritizing an actively maintained project should evaluate the successor or another current tracking server instead.

Your product? Our editors can test FastTrackML in depth and publish a review, labelled as paid · from $149/mo →

FastTrackML pricing

Plans Open sourceFree Free to use — no paid tier required for the core job.

See plans on fasttrackml.io

FastTrackML fact sheet

Free plan	Not verified
Paid from	Free
Run comparison	Not verified
Artifact tracking	Not verified
Dataset versioning	Not verified
Model registry	Not verified
Deployment options	Self_hosted
API and SDK access	Yes
Deployment	Self-hosted
Platforms	Web, Windows, macOS, Linux
Support	Community
Built for	Small business, Mid-market, Enterprise (editorial estimate)
Pricing	Open source
Website	fasttrackml.io
Facts checked	21 Sep 2026

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Featured on iTechGuides

FastTrackML is listed in our ML Experiment Tracking Software directory. Add the badge to your site — it links back to this page.

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Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026

Advertiser disclosure: iTechGuides is reader-supported. Vendors can pay for top positions in our rankings and for a place on other products' pages, and we may earn a commission when you click some links. Bought places stand at the number bought; this page and our disclosure say so. Paying vendors may get a fuller, more detailed review from our editors, and that review can change their score. How we rank.

Last updated 7 Oct 2026 · How we research and update