BoardSnap is an iOS app that turns a whiteboard photo into a structured summary and action plan in ten seconds. For data engineers, that means pipeline architecture sessions, schema design discussions, and data flow diagrams produce written artifacts that survive into implementation — not just a photo in someone's Slack.
Draw the DAG — sources, transforms, dependencies, outputs. Snap. BoardSnap produces a structured description of each pipeline stage, the data flow between stages, and the open engineering questions — the first draft of your pipeline spec.
Draw tables, relationships, indexes, and partitioning strategy. Snap. The summary describes each entity, its attributes, and the design rationale — source material for migration files and schema documentation.
Map where the data comes from, what transforms it, and where it goes. Snap. BoardSnap produces a lineage summary — source, transformation steps, and downstream consumers — the documentation that saves hours when something breaks.
Agree on schema, delivery SLA, and quality guarantees with a downstream consumer team. Snap. The summary becomes the draft data contract — fields, types, freshness guarantees, and escalation path.
Sketch the data quality failure — which table, which upstream, what the anomaly looks like. Snap. BoardSnap produces a structured incident summary with a prioritized fix list — the post-mortem before you've even started writing it.
BoardSnap AI reads DAG-style pipeline diagrams, dependency arrows, and data flow maps. It produces a structured written description of the pipeline architecture — components, dependencies, and data movement — not just a list of node labels.
Paste your data team's wiki, your dbt project docs, or your warehouse schema reference. BoardSnap AI learns your table names, your pipeline naming conventions, and your data team's vocabulary — summaries reference your actual data assets.
Pin your data catalog overview, your current data architecture doc, or your team's data principles. Every future board chat already knows your stack and your standards.
Keep marketing data pipeline work separate from finance reporting and product analytics. Each project has isolated board history and technical context.
Data engineering work happens in all kinds of environments — including data centers and conference rooms with spotty signal. BoardSnap queues captures on-device and syncs when online.
Yes. BoardSnap AI reads DAG-style diagrams — nodes, directional arrows, parallel branches, and dependency annotations. It produces a structured written description of the pipeline components and their execution dependencies.
BoardSnap AI reads entity-relationship style diagrams — table boxes, foreign key arrows, cardinality notation, and column lists. It produces a written description of each table and the relationships between them.
Yes — snap the board at the end of a producer-consumer data contract discussion. BoardSnap produces a structured summary of the agreed schema, delivery frequency, quality guarantees, and open questions — the draft contract both teams can review.
Yes. Draw your data lineage on the board — sources, transformations, outputs, downstream consumers. Snap. BoardSnap produces a lineage summary that serves as the first draft of your lineage documentation — the kind of artifact that makes debugging data quality issues dramatically faster.
Snap the board at the end of the session. Everyone gets the same structured written summary — the shared understanding is documented at the source before anyone re-interprets the data contract differently.
Data scientists using BoardSnap to document experiment design and analysis frameworks.
ML engineers designing training pipelines and model serving architecture.
Backend engineers designing the APIs and services that produce data.
How to document a system design session from a whiteboard.
Snap a whiteboard. Ship the action plan. In ten seconds.