All Pathian analytics begin with direct measurement.

• Uses real operational data, not modeled assumptions

• Anchors analysis to observed system behavior

• Preserves cause-and-effect relationships

• Eliminates reliance on survey-based or portfolio averages

Measurement is the foundation that makes every downstream result defensible.

Pathian normalizes performance against outdoor conditions in real time.

• Eliminates seasonal bias

• Maintains comparability across climates and time periods

• Avoids regression drift

• Supports continuous evaluation without resets

This allows performance to be compared meaningfully — across buildings, systems, and portfolios.

Rather than stopping at whole-building metrics, Pathian analyzes performance at the system and component level.

• HVAC systems

• Airside and waterside components

• Control sequences and operational behaviors

• Equipment-specific performance signatures

This is what enables insight to translate directly into action.

Pathian Curves represent the expected relationship between performance and conditions, derived from real data.

• Built from observed operation, not theoretical models

• Continuously updated as systems evolve

• Comparable across peer groups

• Usable for benchmarking, diagnostics, and verification

Curves provide a shared, statistical language for performance.

GEES organizes Pathian Curves into standardized, peer-based benchmarks.

• Enables apples-to-apples comparison

• Supports system, component, and portfolio views

• Creates a common reference across stakeholders

• Scales from individual buildings to utility portfolios

GEES turns analytics into infrastructure.

Pathian’s technology is designed to support action — not just insight.

• Identifies where opportunity exists

• Quantifies expected impact

• Supports delivery by internal teams or partners

• Verifies results continuously after implementation

Analytics do not end at identification — they persist through verification.

Pathian operates as a platform, not a point solution.

• Cloud-native architecture

• API-accessible analytics

• Compatible with existing control systems

• Designed for utilities, OEMs, governments, and enterprises

The result is technology that integrates into existing workflows instead of replacing them.