Skill Intelligence Engine

See every skill in your organization, in real time

The Problem

Skill data is fragmented across HR systems, self-assessments, and manager reviews. No one has a complete picture of what the workforce can actually do.

The Solution

AI that continuously discovers, validates, and maintains a dynamic skill inventory by analyzing work output, learning completions, and peer signals.

Auditing current skill coverage Knowledge Graph
Inferring skills from work data Retrieval & Embedding
Validating inferred skills Intelligent Tools
Building dynamic profiles Personalization Engine
Maintaining continuous freshness Business Logic Engine
Skill Intelligence Engine Agent Interactive Demo
ACTIVE
Workforce Context Engine
Knowledge Graph

2.4M skill nodes and 18.7M relationships mapping people, jobs, and skills across your organization.

Retrieval & Embedding

Vector-based semantic search finds the right people through meaning, not keywords.

Intelligent Tools

14 specialized tools for matching, predicting, and acting on workforce data.

Personalization Engine

Connects people to roles, learning, and mentors based on skills and goals.

Business Logic Engine

Policy enforcement, approval workflows, and audit trails for every AI action.

Measurable Impact

95% Skill profile completeness
12,400 Hidden skills discovered
Real-time Continuous skill data freshness
FAQ

Common questions

How does the agent infer skills that employees have not self-reported?

It analyzes work output, project contributions, learning completions, collaboration patterns, and code commits to identify capabilities people demonstrate but never formally declare. Most organizations discover 3-4x more skills per employee.

How accurate is skill inference compared to self-assessment?

Inference accuracy exceeds 90% for demonstrated skills. Self-assessments are unreliable because employees under-report skills they take for granted and over-report aspirational skills they have barely used.

Does it understand skill proficiency levels?

Yes. The agent scores proficiency on a spectrum from foundational to expert, based on evidence signals like project complexity, peer recognition, and output quality – not just whether someone has used a skill.

How does it handle skill adjacency and transferability?

The Knowledge Graph maps relationships between 30,000+ skills. It understands that React experience partially satisfies a Vue.js requirement, and that data engineering skills transfer to ML pipeline design.

Can it identify skills gaps at the organizational level?

Yes. It aggregates individual skill profiles to show where your organization has depth vs. gaps, how skill distribution compares to market demand, and where critical capabilities are concentrated in too few people.

You cannot manage skills you cannot see

AI that builds and maintains a complete, living map of every skill in your workforce.