datagallery-ai / dataagent

What it does

• 28 datasource types, ready out of the box. From PostgreSQL, MySQL, Snowflake, BigQuery, and ClickHouse to MongoDB, Redis, and Elasticsearch: connect your existing data stack quickly, cut integration cost, and get the agent into real busine
• Enterprise semantics and context organization. Manage schema, metric definitions, and field relationships in one place, so terms like "GMV" and "retention" resolve to enterprise-approved tables, fields, and definitions — fewer guessed fiel
• Self-hosted deployment and multi-model support. Run it inside your own boundary so data never leaves; on the model side, any OpenAI-compatible provider works (Qwen, DeepSeek, GPT, ...), letting you balance security, cost, latency, and qual
• Safe by default, auditable throughout. Read-only queries, credential isolation, field masking, row limits, and timeouts by default; SQL, tool calls, and event streams are fully persisted and replayable, so every conclusion is backed by evi
• Deep optimization for complex data tasks. Built for multi-table, multi-field, long-horizon analysis and multi-step reasoning: complex questions get decomposed, verified, and converged into trustworthy conclusions, materialized as tables, c