Keep the shared history
The team logs runs to one standard MLflow tracking URI and browses the normal MLflow UI.
Managed MLflow for small teams
Your team trains models and compares runs, but no one owns the tracking server. Trackshund manages that server without adding a larger MLOps platform.
The familiar pattern
Someone starts MLflow on a machine so the team can share experiments. Six months later, that machine is infrastructure and still has no owner.
The visible work: Updates, certificates, user access, artifact storage, and a stable URL.
The less visible work: Checking backups, responding to a failed service, and documenting how the machine was assembled.
One server is often enough.
Invite the next person
Adding another teammate does not trigger another pricing decision.
Stay portable
Trackshund runs standard MLflow, so you keep the MLflow client and experiment format.
A good fit
- You already use or have chosen MLflow.
- Your team wants one shared, private tracking server.
- You value predictable cost and do not want to pay per collaborator.
- Infrastructure work keeps losing to product work.
Probably not a fit
- You need a broader data or model-serving platform.
- You need a compliance programme or formal service commitment already in place.
- You want full control of the host and enjoy operating it.
- You need customer code to run inside the tracking service.
Give your team managed MLflow.
One private server, unlimited members and a bill that stays at $40 a month.