Adding Meaning toIndustrial Data
We're building the intelligence layer for industrial organizations — making OT data accessible, queryable, and meaningful while preserving and growing organizational knowledge—without ever moving it from where it lives.
Our Mission
Industrial operations generate massive amounts of data, but most of it sits unused in silos—locked away in proprietary historians, scattered across SCADA systems, buried in maintenance logs.
We started Conduit because we believe this data has immense value—if only people could access it. Not by building another data lake or yet another ETL pipeline, but by using AI to bring the questions to the data and adapt to any source dynamically.
Our mission is simple: make industrial data accessible to everyone who needs it, without compromising security or sovereignty — while building the organizational intelligence that makes teams smarter over time.
Meaning without movement
What We Believe
The principles that guide how we build Conduit.
Data Sovereignty First
Your data stays where it is. We believe industrial data should never have to move to be useful. Our architecture proves it.
Transparency Over Magic
No black boxes. Every query is deterministic, auditable, and explainable. You always know exactly what Conduit is doing with your data.
Context is King
Raw data is noise. Meaning comes from context—knowing what a tag represents, how it relates to others, and what questions it can answer.
Built for Practitioners
We build for the people who actually use industrial data—operators, engineers, and analysts—not just IT departments.
Context Preservation
Organizational knowledge should outlast any individual. We build systems that capture expertise from actual work and make it available to the entire organization.
Continuous Learning
Every interaction makes the system smarter. Temporal decay keeps knowledge fresh while composite scoring ensures the most relevant expertise surfaces first.
Ready to learn more?
Get in touch to see how Conduit can transform your industrial data operations.