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Conduit — Industrial Context Mesh

The Industrial Context Mesh that adds meaning to your OT data without moving it.

Meaning without movement.

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AnnouncementProduct

Introducing Conduit: The Industrial Context Mesh

We're excited to announce Conduit, a new approach to industrial data integration that adds meaning to your OT data without moving it.

Grey DziubaJanuary 20, 20263 min read
Introducing Conduit: The Industrial Context Mesh

Today, we're excited to introduce Conduit: the Industrial Context Mesh that adds meaning without movement.

The Problem with Industrial Data

Industrial organizations face a fundamental challenge: their operational data is fragmented across dozens of systems. Historians, SCADA platforms, PLCs, MES systems, and enterprise applications all hold pieces of the puzzle. Getting answers requires either:

  1. Moving all data to a central location - expensive, slow, and creates governance nightmares
  2. Building point-to-point integrations - creates technical debt and doesn't scale
  3. Asking data engineers to write custom queries - creates bottlenecks and delays insights

None of these approaches work well. The first two require massive investment. The third means operational insights take weeks instead of minutes.

A New Approach: The Context Mesh

Conduit takes a fundamentally different approach. Instead of moving data, we create a semantic layer that sits above your existing systems and adds context to data where it lives.

How It Works

  1. Connect - Deploy lightweight translators to your existing systems (Splunk, MQTT brokers, OPC-UA servers, and MCP IoT Gateway for PLCs)
  2. Discover - Conduit automatically discovers tags, points, and metadata, building a unified catalog
  3. Contextualize - Define semantic relationships using our ISA-95 inspired ontology
  4. Query - Use natural language through our Natural Query Engine (NQE) to get answers in seconds

No Data Movement

The key innovation is that your data never moves. Conduit's cross-source query engine executes queries directly against source systems and merges results in real-time. This means:

  • No ETL pipelines to build or maintain
  • No data lakes to manage
  • No governance concerns about data duplication
  • No latency from batch synchronization

Natural Language Queries

Perhaps the most exciting feature is our Natural Query Engine (NQE). Instead of writing SQL or navigating complex tag hierarchies, you can simply ask questions:

"Show me the temperature and pressure readings for all fermenters in Building A that exceeded setpoints in the last 24 hours"

NQE understands your semantic model, translates this to optimized queries against multiple source systems, and returns unified results in seconds.

What's Next

Conduit ships with production translators for the most common industrial data sources:

  • Splunk (production, direct SPL compilation)
  • MQTT (production, mqtt.js v5 with topic subscriptions and Sparkplug B)
  • OPC-UA (production, browse/subscribe/read with certificate-based security)
  • MCP IoT Gateway (Modbus, S7, EtherNet/IP, BACnet via AI-powered translators)

All translators run as standalone Docker containers with auto-registration, and NATS provides sub-millisecond real-time data streaming across the mesh.

Get Started

Interested in seeing Conduit in action? Request a demo and we'll show you how to get unified insights from your industrial data in minutes, not months.


Interested in seeing Conduit in action? Contact us to schedule a demo.

Want to learn more about how Conduit can transform your industrial data landscape?

Request a demo