Snowflake

Data

Neotask puts a conversational interface on your Snowflake data warehouse through OpenClaw — query data, manage objects, and run Cortex AI analytics without writing SQL.

What You Can Do

With 16 actions across Snowflake's Cortex, Object Manager, Query Manager, and Semantic Manager, Neotask via OpenClaw gives you full control over your data platform.

Cortex AI Services (3 actions)

  • `cortex_agent` — Run Cortex Agent for intelligent data analysis and multi-step reasoning
  • `cortex_search` — Search across unstructured content stored in Snowflake
  • `cortex_analyst` — Natural language analytics against your semantic models

    • Object Manager (5 actions)

  • Create, drop, describe, and list Snowflake objects (tables, views, schemas, warehouses)
  • Create or alter objects with full DDL control through conversation

    • Query Manager (1 action)

  • `run_snowflake_query` — Execute any SQL against your warehouse with results returned directly

    • Semantic Manager (7 actions)

  • List and describe semantic views
  • Show dimensions and metrics defined in your semantic layer
  • Write and execute queries against semantic views
  • Export semantic view DDL for version control

    • Every action runs autonomously or requires your approval — you decide.

    Try Asking

  • "What were our top 10 revenue-generating customers last quarter? Query the Snowflake data warehouse."
  • "Run this SQL against Snowflake: SELECT product_category, SUM(revenue) FROM orders GROUP BY 1 ORDER BY 2 DESC"
  • "Create a new table in Snowflake called 'weekly_signups' with columns for date, region, and count"
  • "What semantic views exist in our data model and what metrics do they expose?"
  • "Search our Snowflake unstructured data for any documents mentioning supply chain delays"
  • "List all tables in the ANALYTICS schema and describe their column structure"
  • "Query our revenue semantic view to get monthly recurring revenue for the last 6 months"

    • Pro Tips

  • Schedule automated business reports that run Snowflake queries on a morning schedule and post results to Slack — your leadership team gets daily data briefings without analyst involvement.
  • Enable approval gates on create and drop object actions — schema changes in production Snowflake are high-impact and worth human review.
  • Pair Snowflake with MotherDuck in an app group to route ad-hoc analytical queries to the right warehouse based on data location.
  • Use the Cortex Analyst action for semantic-layer queries — it understands your business metrics and returns correctly aggregated answers without raw SQL.
  • Multi-agent teams can build automated data pipelines: one agent creates Snowflake objects, another loads data, and a third validates results before surfacing them.

    • Works Well With