Inside TechWolf’s AI Engine: The 5 layers driving Skills Intelligence

[ TL; DR] 

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What you’ll learn: 

The 5 Layers of TechWolf’s Skill Intelligence

• Labour Market Data Lake – A vast dataset of 1.5 billion job vacancies provides real-time insights into global skill demand and emerging trends.
• Universal Skill Ontology – A structured knowledge graph that maps over 30,000 skills, their relationships, and business relevance.
• Company-Specific Skill Supply – A real-time, AI-driven profile of workforce capabilities, capturing experience, training, and evolving skills.
• Skill Demand Mapping – AI-powered tracking of the skills required for roles, aligned with internal job architecture and external market benchmarks.
• AI-Generated Skill Taxonomy – A structured, hierarchical classification of skills that ensures precision and relevance in workforce planning.

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Introduction: Why workforce skill data needs structure 

As a business or HR leader, you already know that skills intelligence is crucial for workforce planning. Yet, most organizations struggle with fragmented, outdated, or incomplete skill data—making confident talent decisions difficult.

“The challenge isn’t just collecting skills data—it’s structuring it in a way that makes it useful for real decision-making.” – Yasamin Karimi, VP Product

Without a structured approach, HR teams are left guessing about skill gaps, workforce capabilities, and future hiring needs. TechWolf changes the game by providing a scalable AI-driven skill infrastructure, giving companies real-time, structured insights into:

• What skills exist within the workforce
• What skills are needed to meet future business demands
• Where the biggest gaps—and opportunities—lie

Let’s explore how TechWolf structures skill data to enable confident, data-driven talent decisions.

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The 5 layers of TechWolfs’ Skill Intelligence

TechWolf organizes skill data across multiple structured layers, ensuring an accurate and dynamic view of workforce capabilities:

1. Labour Market Data Lake: A global benchmark

TechWolf has built one of the largest proprietary datasets in the world, covering over 1.5 billion job vacancies published over the past nine years. This dataset continuously updates with real-time labour market trends, offering:

• Broad industry coverage across geographies and job functions.
• AI-driven insights that feed skills intelligence models with rich, contextual data.
• Benchmarking & market context to enrich internal workforce data with external labour market trends.

“Relying only on internal skills data is like navigating with half a map. We bring in real-time market intelligence to give companies the full picture.” – Yasamin Karimi, VP Product at TechWolf

TechWolf’s AI-driven data pipeline continuously processes this information, ensuring accuracy and relevance for every skill inference model.

🔍 Curious how TechWolf structures skill data? See it in action.

2. Universal skill ontology: The intelligence behind skill mapping

At the core of TechWolf’s skills intelligence system is its skill ontology—a knowledge graph tracking 30,000+ skills and their relationships.
This enables:

• Skill similarity & adjacency mapping to identify transferable skills.
• Skill hierarchies that define dependencies and specialization.
• Synonyms & definitions that evolve with skill terminology.

“Skills don’t exist in isolation. Our ontology connects them, helping companies understand what skills are truly valuable and transferable.” – Jeroen Van Hautte, CTO at techwolf 

3. Company-specific skill supply: Real-Time Workforce Insights

Every workforce is unique. TechWolf ensures skill data is mapped at an organizational level, with complete security and isolation. The skill supply layer builds a live profile of every employee by analyzing:

• Work experiences
• Training & certifications
• Project participation
• Documentation & outputs

🔄 Dynamic skill timelines track how employees develop and apply skills over time, shifting skill management from a static list to a real-time capability tracker. Whereas a resume only tells part of the story, the skill timeline shows how an employee grows and evolves over time. 

4. Skill Demand: Role Mapping with AI 

On the other side of the equation is skill demand—the skills required for roles within an organization. TechWolf dynamically maps these requirements using:

• Internal job architecture
• Market data comparisons
• AI-driven inference from job descriptions & business needs

TechWolf’s smart governance tools allow HR leaders to refine and adjust skill definitions, ensuring alignment between workforce capabilities and business goals.

📌 Learn more about AI skill mapping [link to blogpost].

5. AI-Generated Skill taxonomy: Structuring skills

To make skill intelligence actionable, organizations need a structured taxonomy. TechWolf’s AI-generated skill taxonomy clusters skill supply and demand, ensuring:

• Full skill coverage with no gaps.
• Optimized granularity, avoiding overly broad or overly specific categorizations.
• Industry relevance, mapped against external labour market trends.

“A well-structured skill taxonomy is the foundation of a skills-based organization. It ensures companies can align talent strategies with business goals.” – Samy B, Head of strategic accounts at techwolf

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TechWolf’s platform allows companies to refine and govern their AI-generated taxonomies, ensuring adaptability over time.

📊 Want to build a custom skill taxonomy for your company? Let’s talk.

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Final thoughts : The future of skills with AI

TechWolf provides a scalable, AI-powered approach to skill data management—helping organizations:

• Understand workforce capabilities with real-time skill profiles.
• Bridge skill gaps by aligning skill supply with demand.
• Leverage AI-driven workforce planning to stay ahead of market changes.

With a strong data foundation, organizations can build smarter talent strategies and truly become skill-based enterprises.

🚀 Ready to future-proof your workforce with AI-driven skills intelligence? Let’s talk.