Client

The client specializes in AI solutions for Infra Asset Management bringing together large-scale data collection and data enrichment with artificial intelligence

Business Requirement

The client required accurate terrain classification to support AI-based infrastructure solutions   looking to improve project efficiency.

Key requirements included:

• Review and modify existing linework based on changes in terrain classification.

• Review, validate, and assign terrain classification on polygon data.

• Maintaining a high-quality threshold of 98% throughout the project.

• Meeting the client’s request for higher efficiency.

RMSI Solution

RMSI developed a comprehensive terrain classification solution for the Kaios project, divided into two main stages: Linework, involving the review and modification of existing linework to account for terrain changes, and Annotation, which encompasses reviewing, validating, and assigning terrain classification to polygon data. The project workflow included training the team on specific requirements and quality standards, performing linework and annotation tasks during the verification/edit phase, ensuring 98% quality through a rigorous 100% quality control process, conducting ongoing quality checks in the QA stage, and ultimately delivering the verified and annotated data to the client.

Technology Used

Kaios Proprietary Applications: Utilized for project management and data handling.

Browser-based application for linework: Used for reviewing and modifying linework.

Citrix Machines: Employed for annotation work, providing remote access and collaboration.

Online Google presentation: Used for query resolution and client communication.

Client Benefits

RMSI’s project resulted in enhanced accuracy for terrain classification, improved efficiency with an expanded team, and comprehensive data coverage. Client satisfaction was high, with effective query resolution, technical troubleshooting, and client input incorporated into the project’s success.