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TechWolf is on a mission to redefine how organizations understand and leverage skills data.
We are dedicated to developing specialized AI that is built exclusively to solve the skills intelligence problem—delivering unparalleled accuracy, fairness, and transparency.
Our AI vision
We envision a world where AI-powered skill data drives workforce transformation, enabling businesses to make informed talent decisions, foster internal mobility, and future-proof their organizations.

Our committment to the AI Act & responsible AI
As part of our commitment to responsible AI, TechWolf aligns with the ISO 42001 standard for AI management and is a proud member of the AI Pact, ensuring we adhere to the highest industry standards for ethical AI development.
Responsible, Transparent, Fair
TechWolf’s AI follows a strict charter that ensures responsibility at every step.
Bias-resistant & fair AI
AI models go through audits to prevent discrimination
Explainable AI
Clear and transparent decisions, not black-box algorithms.
Data security
Protection built into every AI model.
Open innovation
Research and open-source contributions over restrictive patents. ( publishing over patenting)
2.1B+Training Data Points
50+Most-cited AI in workforce intelligence
10K+Research Hours
7Papers published across top AI journals
15Models running in production
5000+Open source downloads
SkillMatch
We construct and release SkillMatch, a benchmark for the task of skill relatedness, based on expert knowledge mining from millions of job ads.
On the Biased Assessment of Expert Finding Systems
This study provides an analysis of how these recommendations can impact the evaluation of expert finding systems.
CareerBERT
Career Path Prediction using Resume Representation Learning and Skill-based Matching
Extreme Multi-Label Skill Extraction Training using Large Language Models
TechWolf leverages Large Language Models (LLMs) to accurately detect both explicit and implicit skills, linking them to a comprehensive skill ontology. Our innovative approach generates high-quality synthetic training data, combined with contrastive learning, leading to a 15-25% improvement in skill extraction accuracy compared to traditional methods.
Ranking the skills required for a Job-Title
In this paper, we describe our method for ranking the skills required for a given job title.
Skill extraction
benchmark for job ads
JobBERT 2
This is a sentence-transformers model finetuned from sentence-transformers/all-mpnet-base-v2 on the generator dataset. It maps sentences & paragraphs to a 1024-dimensional dense vector space and can be used for semantic textual similarity, semantic search, paraphrase mining, text classification, clustering, and more.
Build AI that shapes the future of work
Join a team of innovators driving AI-powered workforce intelligence. Explore opportunities to make an impact.
Blog
Relevant sources
From guides to whitepapers, we’ve got everything you need to for your skills journey.

Why former consultants thrive at TechWolf
How I brought my consulting mindset to TechWolf—and found the freedom to build by Thomas Van Vaerenberg

What UNLEASH America 2025 told us about the future of HR tech
TechWolf’s takeaways from UNLEASH America 2025 | 6-8 May, 2025