Model card creation for ML engineers who document what they ship.
Model card sessions plan the full model documentation — intended use, training data, evaluation results, limitations, and ethical considerations. Drawing the model card structure on a whiteboard with the full team ensures nothing critical gets skipped. BoardSnap captures the outline before documentation begins.
Why ml engineers love this workflow
Model cards are the documentation artifact that makes ML models responsible and maintainable. But they're often written by a single engineer at the end of a project, missing the institutional knowledge that the team developed during training and evaluation. The whiteboard session is where the whole team contributes to what the model card should say.
BoardSnap reads the model card planning board — intended uses, out-of-scope uses, training data characteristics, evaluation results, known limitations, and ethical considerations — and produces a structured model card outline. The documentation reflects the team's collective knowledge.
The exact flow
- Define intended and out-of-scope uses
Write explicitly what this model is designed to do and, critically, what it should not be used for. Out-of-scope uses require the same care as intended uses.
- Document training data characteristics
Describe the training data — sources, time range, demographic coverage, known gaps. Be honest about what's missing.
- Summarize evaluation results
Write the key evaluation metrics, the benchmark datasets, and the performance across different subgroups. Disaggregated results matter.
- Name known limitations and failure modes
List the conditions under which the model underperforms. This is the most important section — be specific.
- Snap the model card planning board
Open BoardSnap and capture. The full model card outline is documented before writing begins.
What you'll get out of it
- The full team contributes to model card content — not just one engineer
- Intended and out-of-scope uses are defined with team consensus
- Known limitations are documented honestly before the model ships
- The model card outline serves as a documentation checklist
- Model card history shows how documentation evolved across model versions
Frequently asked
What are the required sections of a model card?
The Mitchell et al. (2019) model card framework recommends: model details, intended use, factors, metrics, evaluation data, training data, quantitative analyses, ethical considerations, and caveats. BoardSnap reads whatever sections you write on the board.
How does the whiteboard session improve model card quality?
When the whole team contributes, the model card reflects knowledge that's distributed across data scientists, ML engineers, and product managers — not just the person assigned to write the documentation. BoardSnap captures that collective knowledge from the whiteboard session.
Can I share the model card outline with legal or compliance teams?
Yes. The BoardSnap output is in plain English. Legal and compliance reviewers can read the intended use, limitations, and ethical considerations sections without ML expertise.
How do I go from the BoardSnap outline to a finished model card?
Use the BoardSnap structured output as the draft model card. Each section on the board becomes a section in the document. Add quantitative results from your experiment tracking tool to complete it.
ML Engineers: try this on your next model card creation.
Three taps. Action items in your hand before the room clears.