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TReqs by roar + GLaaS
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Training Lineage You Can Actually Trust

When your last model run breaks prod, can you explain exactly what changed?

roar observes every run automatically. GLaaS stores lineage as source of truth. TReqs adds lightweight coordination for training requests. No code changes. No framework constraints. No lock-in.

Install roar See how it works

The Tension You Already Feel

Most ML teams do not fail because of model quality. They fail because nobody can prove what happened.

Cloud credits disappear

You rerun experiments because the last ones are not reproducible.

Results drift silently

Metrics shift and nobody can point to one clear change.

Artifacts lose context

Checkpoints exist, but the config, data slice, and code state are unclear.

Scale adds chaos

More people and more runs means less shared understanding.

How It Works

Install one CLI tool, run training as usual, and get automatic runtime observation.

$ pip install roar-cli
$ roar run train.py --config configs/base.yaml

observing runtime...
captured: code commit, config diff, env, dataset refs,
metrics, checkpoints, runtime events
lineage synced to GLaaS

Captured automatically

  • Code version and dependency footprint
  • Config and hyperparameter changes
  • Dataset references and artifact lineage
  • Metrics + runtime timeline

What You Get

Source of truth for runs

Each run is traceable without extra process overhead.

Reproducibility

Rebuild results from known inputs and known code state.

Change visibility

See what shifted between runs without detective work.

Artifact traceability

Track checkpoints and outputs back to exact runtime context.

TReqs: Just Enough Structure

TReqs is a lightweight coordination layer for training requests. It is not orchestration software and not another platform migration.

Request tracking

Capture what was requested, by whom, and why.

Run linkage

Connect each request to actual lineage-backed runs.

Minimal process

Keep the team aligned without heavy workflow software.

CLI-first

Fits existing stacks and existing engineer habits.

Pricing

Simple tiers. No hidden model-run tax.

Free

$0 / individual

  • CLI install + local observation
  • Single-user lineage history
  • Basic troubleshooting context

Team

$49 / user / month

  • Shared lineage workspace
  • API access + run comparisons
  • TReqs coordination layer

Enterprise

Custom

  • SSO + policy controls
  • Dedicated support and onboarding
  • Private deployment options

Install roar and run it on your last training job.

You should know exactly what changed before your next release.

Install roar