I built Asset Language after spending 5+ years at Element Analytics, where I led development of their industrial knowledge graph and digital twin capabilities.

At Element, I saw firsthand how data teams struggled with the same problem everywhere: weeks spent decoding cryptic historian tags before any real analysis could begin. Even with sophisticated data fabric solutions, the fundamental issue remained. The engineering context trapped in design specifications never made it to the data layer.

The irony is that all that context already exists in P&IDs. Process engineers have documented every equipment relationship, every tag, every connection. But data teams end up deriving new data models based on scattered documentation systems, manually maintained spreadsheets, and plant floor knowledge. And when there's a new project, they have to do it all over again.

Asset Language solves this problem at the source. Instead of building another metadata layer on top, we make your P&IDs directly executable by creating a live semantic bridge that translates raw sensor streams into queryable, business-ready data.

Before Element, I spent 15 years building mission-critical software for healthcare operations, where I learned that reliability and clarity matter more than complexity.