Use Cases / AI Readiness / Case Study
CASE STUDY
Preparing Enterprise Data for AI Agents.
How a major real estate organisation improved information quality to build a stronger foundation for AI-driven processes.
Industry
Real Estate & Property
Use Case
AI Readiness & Data Optimisation
The challenge.
A major real estate organisation wanted to introduce AI agents to automate business processes and improve decision-making. However, it recognised that the effectiveness of these agents would depend on the quality, relevance and reliability of the information available to them.
Before deploying AI, the organisation needed to identify and address redundant, obsolete and trivial (ROT) data across its information estate.
The DataBelt solution.
DataBelt was deployed to undertake a comprehensive data-quality and optimisation exercise.
The platform discovered and categorised information, identifying unnecessary duplicates, documents beyond their applicable retention periods and information with little or no continuing business relevance.
Using DataBelt's EDM tools, information identified for review was moved to a designated location where business owners could validate the proposed ROT classifications before approved records were permanently deleted.
Throughout the process, DataBelt's Data Quality Index provided a measurable way to track improvements and demonstrate progress.
The outcome.
The organisation established a cleaner, more reliable information environment, supporting the successful deployment of its AI agents.
By improving data quality before introducing automation, the business strengthened the foundations for more accurate, consistent and repeatable AI-driven processes.
