For Data Scientists

For data scientists who design experiments before they run them.

BoardSnap is an iOS app that turns whiteboard photos into structured summaries and action plans in ten seconds. For data scientists, that means experiment design sessions, feature engineering discussions, and hypothesis frameworks produce written artifacts — not just a board photo that gets buried in a Slack thread.

Download on the App Store Free to start. Pro from $9.99/mo or $69.99/yr.

What hurts today

  • Experiment design sessions produce a clean hypothesis, metric definition, and success criteria on the board — then someone re-interprets them differently when setting up the experiment
  • Feature engineering discussions involve a lot of visual thinking — transformations, interactions, distributions — that's hard to capture in meeting notes
  • Model evaluation framework sessions produce clear methodology decisions that don't make it into the model card or experiment log
  • Stakeholder alignment sessions about what question we're actually answering require re-running the whiteboard explanation every time a new person joins the project
  • A/B test planning boards — treatment groups, sample size rationale, statistical approach — generate decisions that should be in the experiment record but rarely are
  • Cross-functional data discussions where engineering, product, and data science are all at the board produce different mental models in each team

How BoardSnap helps

  • Snap an experiment design session and get a structured summary — hypothesis, metric definition, success criteria, and implementation action items — ready for your experiment tracking system
  • Feature engineering decision boards produce a written rationale for why each feature was included, transformed, or excluded — the kind of documentation model cards are supposed to have
  • A/B test planning boards produce a structured experiment brief: treatment definition, sample size rationale, statistical approach, and the analysis plan
  • Brand-aware AI writes summaries using your team's actual metric names, your data pipeline terminology, and your modeling framework vocabulary
  • Pin your current research questions and success metrics so every future board chat already knows what you're trying to measure and why
  • Cross-functional whiteboard sessions produce a single written summary — data science, engineering, and product all working from the same documented understanding

A day with BoardSnap

  1. Experiment design

    Write the hypothesis, the treatment design, and the success metrics on the board. Snap. BoardSnap produces a structured experiment spec — hypothesis, intervention, metric, and decision criteria — ready for your experiment tracking tool.

  2. Feature engineering session

    Sketch the feature transformations, the interaction terms, and the encoding decisions. Snap. The summary captures each feature decision and its rationale — the first draft of your feature documentation.

  3. Model evaluation framework

    Map the evaluation metrics, the test dataset strategy, and the baseline comparison on the board. Snap. BoardSnap produces a structured evaluation plan that becomes the methodology section of your model report.

  4. Stakeholder alignment

    Work through what question we're actually trying to answer, what a good outcome looks like, and what decisions the analysis will enable. Snap. The summary is the project brief everyone can reference — no re-explaining the analysis objective.

  5. Results walkthrough

    Sketch the key findings, the interpretation, and the next steps on the board. Snap. The summary becomes the analysis memo — findings, interpretation, and recommended actions structured and ready to share.

Features that matter for data scientists

Diagram and annotation reading

BoardSnap AI reads distribution sketches, decision tree diagrams, feature interaction matrices, and annotated graphs on whiteboards. It produces structured descriptions of the analytical content — not just a list of words.

Brand-aware AI

Paste your team's internal wiki, your metric dictionary, or your modeling framework documentation. BoardSnap AI learns your metric names, your experiment terminology, and your analytical vocabulary — summaries reference your actual work.

Pinned context

Pin your research questions, your north-star metric definition, or your current experiment log. Every board session chat already knows the analytical context — ask follow-up questions that get grounded answers.

Projects per research area

Keep recommendation system experiments separate from fraud model development and pricing analysis. Each project has isolated board history and context — the AI chat gives answers scoped to the right analytical domain.

Auto-generated subtasks

High-level experiment tasks break into concrete implementation steps: write the data pipeline, implement the feature transformations, set up the evaluation harness, run the baseline comparison.

Frequently asked

Can BoardSnap capture a statistical framework or decision tree drawn on a whiteboard?

Yes. BoardSnap AI reads decision tree structures, probability diagrams, and annotated statistical frameworks. It produces a written description of the decision logic and the key analytical choices — useful for documenting methodology before coding it up.

How does it help with experiment design documentation?

Run your experiment design session at the whiteboard — hypothesis, treatment, metrics, success criteria. Snap. BoardSnap produces a structured experiment brief that serves as the source for your experiment tracking system entry. It's the 'design doc' you'd otherwise write from memory afterward.

Is it useful for model documentation and model cards?

Yes — snap the feature engineering session, the evaluation framework discussion, and the model architecture board separately. Each produces a structured artifact. Combine them to build the model card instead of writing it from scratch after training.

Can I use it for cross-functional data alignment sessions?

Yes. Snap the board at the end of a data science + product + engineering whiteboard session. Everyone gets the same structured written summary — the shared understanding is documented at the source before anyone re-interprets it.

What if my board is mostly equations and notation?

BoardSnap AI reads mathematical notation on whiteboards reasonably well — variable names, equations, and statistical notation. Dense mathematical derivations produce more limited output than conceptual diagrams with annotations, but mixed boards (concept + equation) work well.

Built for data scientists who ship.

Snap a whiteboard. Ship the action plan. In ten seconds.

Free · 1 project, 30 boards Pro $9.99/mo · everything unlimited Pro $69.99/yr · save 42%
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