OEM platforms already understand their equipment, data models, and control semantics. The challenge is not access — it is transforming raw system telemetry into economical, scalable performance intelligence without disrupting existing architectures.

The OEM Embedded Analytics Engine integrates directly into OEM platforms, embedding Pathian’s benchmarking and weather-normalized performance mathematics while preserving native data structures, naming conventions, and control behavior.

The engine applies statistically derived, weather-normalized mathematics to real operational data, enabling OEMs to evaluate performance across assets, portfolios, and time without relying on costly digital twins or site-specific models.

Because analytics are based on standardized, weather-normalized mathematics rather than site-specific simulations, new performance algorithms can be developed and deployed in days rather than years.

A simple example is fan laws. When combined with weather-indifferent normalization, these well-understood physical relationships allow fan performance to be benchmarked consistently across buildings, systems, and geographies. This makes it possible to compare fan performance globally using measured behavior — something site-specific digital twin approaches cannot do economically or at scale.

This approach allows OEMs to:

• Identify service opportunities at scale

• Quantify performance gaps and degradation

• Validate improvement after service or retrofit

• Support equipment upgrade and replacement decisions

All using measured behavior rather than modeled assumptions.

The OEM Embedded Analytics Engine is designed to integrate cleanly into existing OEM analytics stacks without forcing structural alignment or refactoring.

OEM platforms can request normalized performance outputs at multiple levels of resolution — using their own naming structure throughout — including:

• Group and portfolio level

• Subgroup and site level

• Equipment level

• Component level

• Individual point level

This allows Pathian analytics to power OEM benchmarking wherever it fits naturally within OEM applications, from high-level portfolio views to detailed diagnostics, without duplicating analytics or restructuring systems.

The engine operates alongside existing OEM systems rather than replacing logic, control strategies, or applications.

• Native data models are preserved

• OEM naming conventions remain unchanged

• Control semantics and execution logic are untouched

• No point renaming or data restructuring is required

Normalized performance outputs are cataloged using Pathian’s internal reference system, allowing results to remain comparable across assets and product lines without altering OEM architectures.

The engine supports design-specific and component-level benchmarks that reflect how equipment is intended to perform under real operating conditions.

This enables OEMs to embed analytics aligned with engineering intent — not generic averages — while maintaining consistency across deployments, product families, and customer environments.

Analytics generated by the engine can be:

• Integrated directly into OEM analytics and applications

• Used to support service identification and diagnostics

• Applied across deployed fleets and portfolios

• Leveraged to support lifecycle services and equipment sales

By embedding standardized, weather-normalized benchmarking at the analytics layer, OEMs gain a scalable foundation for performance transparency and recurring value creation — without sacrificing architectural control.

The OEM Embedded Analytics Engine allows OEMs to monetize performance intelligence at scale — without the cost, complexity, and fragility of digital twin approaches.

It provides an economical, integration-friendly path to benchmarking, opportunity identification, and performance validation while preserving full ownership of customer relationships, naming structures, and system behavior.