INDUSTRIAL DATA PLATFORM
Collect, process, model, and distribute factory data
Tier0 is an industrial data platform for manufacturing. It turns fragmented data from machines, OT systems, and business applications into a structured, reusable industrial data foundation — ready for downstream use.
01
Collect
Data from machines, PLCs, SCADA, MES, ERP, and more
02
Process
Standardize, and model it into a reusable industrial data foundation
03
Distribute
Structured data to downstream applications, analytics, and AI
THE CHALLENGE
Why factory data stays fragmented
Manufacturing environments produce a large amount of operational data.
Factory data is scattered everywhere
Machine signals, system exports, and operational records live in separate silos — historians, local databases, shared drives, and spreadsheets. There is no consistent, shared source of truth.
Every project builds its own integration
Each new dashboard, report, or application requires connecting the same data sources from scratch. Integration logic is duplicated across teams and projects with no shared reuse.
Collected data is rarely structured for reuse
Data may be captured, but without consistent models, naming conventions, or context, it remains difficult to use reliably across different applications or teams.
Short-term fixes become long-term complexity
Point-to-point connections and isolated pipelines accumulate over time. Scaling digital initiatives becomes slower and more fragile with each new use case added.
Step 1 — Collect
Collect data across
the entire factory
Tier0 connects to a wide range of industrial and business data sources — from machines and control systems on the factory floor to ERP and operational databases in the back office. Both real-time operational data and transactional business data flow into one industrial data platform.
One ingestion layer for all factory data.
Tier0 supports standard industrial protocols, database connectors, and REST APIs — so teams can start connecting data without rebuilding the same infrastructure for each project.
SCADA Systems
MES
SQL Databases
WMS / Warehouse
Spreadsheets & Files
PLCs
Historians
ERP Systems
REST APIs
CMMS / Maintenance
Energy Monitoring
Custom Protocols
Transform and Normalize
Convert raw payloads into consistent formats. Normalize units, tag names, and structures across heterogeneous sources.
Filter and Route
Apply rules to route specific events and values to the right downstream destinations — without hardcoding logic in every application.
Enrich with Context
Attach operational or business metadata to raw data. Turn a raw signal into meaningful, labeled information tied to an asset, line, or process.
Standardize for Reuse
Prepare data once in a consistent, well-defined structure so it can be reliably consumed by multiple downstream systems without additional transformation.
Step 2 — Process
Process industrial data for real use
Collecting data is only the first step. Tier0 processes industrial data as it flows — transforming, filtering, enriching, and routing it so it arrives at the right place in the right format.
Raw machine output and system exports rarely arrive in a usable form. Tier0's processing layer handles the gap between raw ingestion and downstream usability — without requiring each application to implement its own transformation logic.
Step 3 — Model
Model data into a reusable industrial foundation
Tier0 doesn’t just store data — it gives industrial data structure and operational meaning.
Data is organized around real manufacturing entities such as sites, work areas, lines, assets, processes, and data points. This creates a shared model that every downstream application, report, workflow, and AI use case can build on.
Industrial Data Model Hierarchy
Sites
Work Areas
Lines & Cells
Assets
Processes
Mapped to Operations
Organize data around real manufacturing entities — sites, work areas, lines, assets, processes, and data points.
Consistent Across Systems
Use one shared structure instead of separate naming rules and data logic across different systems.
Reusable Across Projects
Build dashboards, workflows, analytics, and AI applications on the same operational context.
No New Silos
New use cases extend the same data foundation instead of creating another isolated data layer.
Operations Dashboards
Real-time plant and line visibility
Event Subscribers
Alert systems and notification services
Analytical Tools
BI platforms, reporting, and data exploration
Workflow Engines
Process automation and digital workflows
External Systems
Third-party platforms, APIs, and integrations
AI Pipelines
ML models and AI inference workflows
Step 4 — Distribute
Distribute structured data to downstream consumers
Tier0 is not a dead-end data repository. Once industrial data is collected, processed, and modeled, it can be published to the systems, applications, and users that need it.
Dashboards, workflows, analytics tools, external systems, and AI pipelines can all subscribe to the same operational data layer.
Tier0 uses a publish / subscribe model, so systems can receive real-time updates as data changes — without polling or one-off connectors.
Why It Matters
The operational impact of a structured data foundation
Less repeated work
Fewer
one-off integrations
A shared data layer eliminates the need to rebuild connectivity and transformation logic for every new application or project.
Better consistency
Consistent data
across use cases
With a single structured model, all teams and applications work from the same definitions, names, and values — reducing errors and misalignment.
Faster delivery
Shorter time
to working solutions
When data is already connected, processed, and modeled, new applications and reports can be built in days instead of weeks.
Long-term foundation
Infrastructure
that scales
A structured industrial data foundation grows stronger with each new use case, rather than accumulating complexity and technical debt.
