Track experiment follow-ups
Connect
SPIRITT
Weights & BiasesWeights & Biases activity.
An organized ML operation.
SPIRITT works with Weights & Biases to build project directories, run-state boards and experiment follow-up systems from the metadata your ML team already maintains.
What you can do with Weights & Biases.
Make experiment activity visible
Track run identities, states and creation times across selected projects, with freshness and pagination handled explicitly.
Organize the research estate
Connect projects, reports, sweep listings and artifact types into a searchable operational index.
Route the next action
Turn failed-run states and ownership gaps into tasks in connected tools, keeping experiment data and workflow state separate.
Works with your other apps.
Get started in three steps.
01
Open your workspace
Start a SPIRITT workspace for your Weights & Biases workflows and the connected tools that support them.
02
Connect Weights & Biases
Connect Weights & Biases with access to the records and resources your mission needs. Keep the account scope aligned with the work you delegate.
03
Delegate an outcome
Hand over a mission such as: build a run-state operations board. SPIRITT builds the workflow, coordinates the connected tools, and follows through on the result.
Hand over a mission.
Choose a mission. Make it yours.
Put Weights & Biases to work.
An organized ML operation
Questions
Weights & Biases, with SPIRITT.
01What can I delegate with Weights & Biases and SPIRITT?+
Build project directories, run-state boards and experiment follow-up systems from the metadata your ML team already maintains. SPIRITT connects those capabilities to working apps, coordinated tasks and a maintained record of outcomes.
02How do I connect Weights & Biases?+
Open a SPIRITT workspace, connect Weights & Biases, and give it access to the records or resources your mission needs. Describe the outcome, the source of truth and the actions you want it to own. Existing account access determines which operations are available.
03Which tools work well alongside Weights & Biases?+
Useful combinations include GitHub to track experiment follow-ups, Slack to route failed-run states, Notion to index research projects. SPIRITT coordinates each separately connected app and keeps source references with the resulting work.
04Can it read run metrics or training history?+
This connection lists run IDs, names, states and creation times. It does not return run configuration, metrics or history, so dashboards focus on operational state rather than model quality.
05Can it start training or change runs?+
No run or artifact writes are exposed here. SPIRITT can coordinate next steps in connected development tools using the available run and project metadata.
06What can it learn about automations?+
It can list accessible automation metadata and integration names. That supports a coverage inventory, not proof that an automation fired or permission to change its configuration.