Industrial Data That’s AI-Ready for Snowflake

Connect plant-floor systems and prepare operational data for Snowflake analytics, AI, and manufacturing intelligence.

• Connect PLCs, SCADA, historians, sensors, CNCs, MES, and production systems
• Use 250+ native drivers to reduce custom integration
• Consistent data foundation for Snowflake Data Cloud and analytics workflows

Turn raw machine signals into structured operational data before sending it to Snowflake.


• Normalize tags, units, timestamps, and data types
• Add asset, line, machine, work center, and process context
• Prepare high-quality data for Snowflake tables, dashboards, and AI workflows

Move industrial data from Litmus Edge into Snowflake using ingestion patterns built for continuous data movement.

• Send contextualized data into Snowflake tables and schemas
• Support Snowpipe and Snowpipe Streaming ingestion patterns
• Enable reliable edge-to-cloud delivery with store-and-forward behavior

Send governed OT data into Snowflake without rebuilding custom pipelines for every plant.

• Stream contextualized machine data into Snowflake
• Support real-time visibility and historical analysis
• Standardize data pipelines across sites and production systems

Prepare industrial data so Snowflake AI and analytics workflows can support manufacturing decisions.

• Deliver contextualized OT data into analytics and AI workflows
• Combine plant data with ERP, MES, supply chain, quality, and enterprise data
• Enable Snowflake Cortex AI, Snowpark, and ML use cases

Run processing close to machines for faster and cleaner industrial data into Snowflake.

• Filter, enrich, and transform data at the edge
• Run KPIs, alerts, thresholds, and event logic locally
• Send only the data needed for Snowflake analytics and AI