Global Asset Management Firm

The Challenge

A global asset management firm struggled with inconsistent infrastructure data. As the company began investing heavily in AI and predictive analytics, it became clear that their fragmented asset records—spreadsheets, PDFs, and photos— were not only slowing them down, but limiting innovation and increasing customer acquisition costs.

A Closer Look

Without a shared language or system of record for asset data, the firm’s adoption of AI slowed, risk was introduced into planning models, and senior engineers were forced to manually validate data. The tangible result is that, before deploying EMPEQ, the firm was struggling with: • Several year-long data cleanup cycles.

• Several year-long data cleanup cycles. • High inventory costs stemming from lack of

• Empowered analytics, compliance, and operations teams to work from the same data fabric to increase business continuity. • Enabled analytics teams to access validated,

• Lack of granular data to fuel financial reporting. • Poor quality data supporting ROI calculations—

• Lowered cost of acquisition and survey rework by over 25%. • Activated AI models to identify risk, optimize

over 25%. • Activated AI models to identify risk, optimize spend, and inform CapEx strategy. • Empowered analytics, compliance, and

The Solution

• Animated and monetized dormant historical asset records to create additional revenue streams.

Asset Types Mechanicals, Electrical,

Mechanicals, Electrical, Envelope, Lighting

Strategic Outcome Asset Data Fueled AI;

Asset Data Fueled AI; 25% Decrease in CAC

Commercial, Multifamily

Company Type Global, Publicly-Traded

Structured Asset Intelligence, Delivered at Global Scale

engagement@empeq.co (347) 903-6737