From Spreadsheets to Insights: ​Turn Disconnected Skills Data into Intelligence

iMocha unifies fragmented data from resumes, HR systems, and employee inputs into a centralized skills ontology, enhanced with AI-enriched skills intelligence metadata, enabling structured workforce planning and agile decision-making.

The taxonomy follows a 4-level hierarchy—Domain, Sub-domain, Skill Clusters, and Skills—tagged with rubrics, certifications, and metadata. It’s aligned with O*Net, Singapore Skills Framework, and industry-specific models.

iMocha’s AI engine continuously discovers and updates emerging skills by analyzing adjacent skills, resume, certification, employee request and job profile, ensuring taxonomies reflect real-time industry shifts.

Yes. Through adjacent skills mapping, iMocha reveals contextual relationships between skills, enabling rapid redeployment, project-based resourcing, and internal mobility across functions.

Each job profile is mapped to granular skill sets and required proficiency levels, forming a role-skills-capability graph that supports workforce strategy, L&D planning, and hiring benchmarks.

By standardizing and enriching skills with descriptive metadata, iMocha removes duplication, improves clarity, and brings consistency across departments and business tools.

By uncovering hidden adjacencies and contextual skills, iMocha helps spot talent with transferable capabilities—ideal for lateral moves, cross-functional assignments, or leadership pathways.