Your databases.
Their happy place.

For each business entity Lily writes the everyday queries you actually run — "recent orders for a customer", "find by email" — parameterized and ready to open in the editor. Read-only and EXPLAIN-validated before they're ever offered; generated on demand when you explore an entity.

Describe a change in plain language — "add soft-delete", "make email unique" — and Lily generates the forward DDL plus its exact rollback, grounded in your real columns, keys and indexes. Nothing runs until you open it in the editor and confirm; destructive changes are flagged and pass the same write guardrails as any statement.

Ask "where do we store refunds?" and Lily ranks the real tables and columns that hold the concept — each with a one-line reason — searching your schema's meaning, not just its names. Click a result to jump straight to the table. It searches metadata only, never your rows.

Before any UPDATE, DELETE, TRUNCATE, or DROP, Lily estimates how many rows it will touch and which tables it reaches by foreign key — without ever running the write. The riskiest ones (no WHERE, TRUNCATE, DROP) make you type the table name to confirm.

Lily flags columns holding personal data — CPF/CNPJ, cards, emails, phones — using local format fingerprints, and automatically redacts them before any AI feature ever samples a row. Your data never leaves your machine for the classification.

PostgreSQL, MySQL/MariaDB, SQLite, SQL Server, Redis, MongoDB, DynamoDB, Trino, and ClickHouse — each with a UI tuned to its data model. SSH tunnels support agent, key-passphrase, and password auth for corporate bastions.

Sort any column (numbers, dates, and text handled right) and filter with real operators — no re-query. Freeze the first columns while the rest scroll, click a header for instant count/sum/avg/min/max, chart the result, or let local AI summarize the patterns.

Audit any database with ready-to-run fixes plus an AI architecture review — schema, index, and security rules (RLS, PUBLIC grants, unused indexes) for relational, TTLs and big keys for Redis, indexes and document size for MongoDB. Jump from a value to the row it references, kill stuck queries, and render any plan as a visual EXPLAIN cost-bar tree.