Manufacturing Design Is Your Data Interface
For data teams at process manufacturers, the hunt for context is a familiar story: weeks spent decoding cryptic sensor tags and reverse-engineering data models before critical analysis can even begin.
This painstaking work happens because the source of truth for operations—the P&ID—is treated as a static document. Every instrument tag, equipment ID, and process connection documented by your engineers represents a structured data relationship. But this knowledge is trapped, forcing data teams to rebuild it from scratch.
We believe there's a better way. Your engineering designs are the blueprint for your data model. Asset Language makes that model executable. We transform your P&IDs into queryable structures that connect your historian to platforms built for high-value analytics and ML, making your design the organizing principle for your data.
From Documentation to Data Infrastructure
By making P&IDs executable, we provide four core capabilities:
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1.
Query in Business Language
Query equipment directly, eliminating weeks of tag decoding. Use business language like
reactor.temperatureinstead of sensor tags designed for machine interfaces. -
2.
Automated Data Structuring
Make P&IDs the organizing principle. We automatically parse equipment hierarchies and connections, creating a live semantic bridge that translates raw sensor streams into queryable, business-ready data—eliminating the need for brittle spreadsheet-based mapping tables.
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3.
Maintain Governance
Version control for P&IDs and sensor tags keeps your data infrastructure synchronized with plant floor reality as it evolves.
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4.
Seamless Cloud Integration
Deliver clean, analytics-ready data feeds to platforms built for high-value analytics: Snowflake, Databricks, and AWS IoT SiteWise.
The Difference in Practice
Traditional Approach:
Data teams receive thousands of sensor tags via spreadsheets. They spend weeks reverse-engineering which tags belong to which equipment, coordinating with operations to understand naming conventions, and manually building mapping tables. This work repeats for every new project, every analytics initiative.
With Asset Language:
A data engineer queries: reactor.temperature and receives data streams in minutes.
Process experts validate using familiar equipment IDs while automation accelerates their review work.
The P&ID visualization catches broken tag mappings before they silently break analytics.
The Paradigm Shift
This isn't just faster data integration. It's a fundamentally better way to build industrial data infrastructure. When your engineering source of truth drives the data structure directly, analytics stay aligned with operations, changes propagate systematically, and the barrier between engineering and data teams dissolves.
Your P&IDs already define the relationships that matter. Asset Language makes them executable, giving your teams direct access to manufacturing data that's structured to reflect how your plant actually operates.
Enrique Meneses
Founder & Head of Product