ML Training Control Plane
Governed training on MLflow-backed infrastructure.
Logix launches and monitors Training Jobs, governs MLflow tracking and registry operations, and keeps each Entity's self-hosted training workspace auditable.
MLflow-backed tracking and registry
Permissioned Training Job operations
Compose-first, Kubernetes-ready path
Recent Runs
transformer-finetune-v3acc: 0.942Completed
baseline-lr-grid-searchloss: 0.231Completed
ablation-attention-dropoutf1: 0.887Running
prod-model-retrain-q3auc: 0.973Staged
Core Capabilities
Control training without losing MLflow compatibility.
Logix composes orchestration, storage, permissions, and audit around MLflow so teams can launch Training Jobs and operate the model lifecycle from one governed surface.
Training Job Control
Launch, monitor, cancel, and audit entity-scoped Training Jobs from one governed control plane.
MLflow-Backed Tracking
Use MLflow as the canonical source for experiments, runs, metrics, artifacts, and model registry state.
Permissioned Registry Ops
Register models and transition model versions through explicit Logix Permissions and Audit Events.
Self-Hosted Workspace
Run a Compose-first stack with production-shaped storage and orchestration that can move toward Kubernetes later.
The Training Workflow
Launch, observe, and register — all from one place.
Logix uses MLflow where it is strongest, then adds the missing control-plane pieces for self-hosted training execution and governed model operations.
01
Launch
Start a Training Job from a Git-backed code reference, prebuilt Training Environment, Dataset Reference, and approved resource profile.
02
Observe
Follow job state, lifecycle events, logs, and linked MLflow runs without exposing raw secret values in job details.
03
Register
Operate MLflow-backed registered models and model versions with capability-specific permissions and audit history.
Early Access
Ready to control self-hosted ML training?
Logix gives your team the control-plane layer around Training Jobs, MLflow-backed tracking, registry operations, and audit history.
Built with purpose
Meet the team behind Logix.
A small, focused group of ML practitioners and engineers building a practical control plane for reproducible, governed training.
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5 core members across engineering, product, and design.