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Query Trino data with natural language and schema-aware SQL.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "Enterprise Big Data Copilot" yet — see the docs or source repo.
Convert “order volume by region in the last 7 days” into Trino SQL, and ensure the fields match the schema.
Validated Trino SQL that matches the schema.
Show the tables, columns, and available metadata for this data source so I can write analysis SQL.
A metadata summary for modeling and querying.
Use the profiling tool to analyze the performance bottlenecks of this Trino query and suggest optimizations.
A query performance analysis with optimization suggestions.
Data analysts can describe a metric in plain language and get executable Trino SQL. It is useful for ad hoc extraction and fast metric validation.
Developers can inspect tables and columns before writing queries, reducing errors from schema changes. Schema-aware SQL generation also improves accuracy.
When a Trino query becomes slow, the profiling tool can help identify bottlenecks. It suits scenarios where teams need to locate and optimize slow queries.
It targets Trino big data platforms, supports natural-language queries, and generates validated, schema-aware SQL. It also exposes metadata, query, and profiling tools through MCP.
Based on the description, it depends on a Trino data platform and uses local LLM inference with RAG. See the source repository for exact setup requirements.
It emphasizes schema-aware and validated SQL to reduce generation errors. It also provides metadata and profiling capabilities, not just one-off query rewriting.
Execute SQL on Trino clusters securely through MCP with read/write controls.
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