# 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.
- High inventory costs stemming from 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 spend, and inform CapEx strategy.

## The Solution

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

### Asset Types

- Mechanicals, Electrical, Envelope, Lighting

### Strategic Outcome

- Asset Data Fueled AI;
- 25% Decrease in CAC

### Company Type

- Global, Publicly-Traded

### Structured Asset Intelligence, Delivered at Global Scale

📧 [engagement@empeq.co](mailto:engagement@empeq.co)
📞 (347) 903-6737