Datascale

Datascale is a web-based platform that functions as an AI-native data design tool, combining the interactive visual capabilities of a diagramming tool like Miro with the code-awareness of an AI assistant like Cursor, specifically tailored for databases and data architecture. The core purpose is to help software engineers and data professionals design, document, and collaborate on data schemas, relationships, and flows without requiring manual mapping or external migrations. Users begin by connecting their existing SQL code or database schemas — Datascale automatically reverse-engineers the entire data architecture, identifying tables, columns, foreign keys, JOINs, and lineage dependencies. This process eliminates the need for manual reverse engineering or framework changes, providing instant visual insights into complex relational structures. Once the schema is imported, everything is displayed on a single infinite canvas where users can combine three types of representations: data relationship diagrams (ERDs), wiki-style documentation pages, and flowcharts. Nodes representing tables or fields can be dragged, selected, resized, and connected with lines to illustrate foreign key references, cascading dependencies, or custom relationships. A key differentiator is the AI-native collaboration layer. Users can drag-select any group of nodes on the canvas — for example, all tables related to a specific business domain — and then open a chat panel to ask the AI questions in natural language. The AI understands the underlying schema and can answer queries like “What foreign keys connect these two tables?” or “Suggest a normalized design for this set of fields.” It can also generate SQL snippets, rewrite table structures, or propose modifications to the schema directly. This cha