WeNet · Project

AI Platform That Matches Diverse People to Solve Problems Together

digitalTestedTRL 5Thin data (2/5)

Imagine you need help with something but the best person to ask isn't in your usual circle — they're from a different culture, background, or skillset. WeNet built an AI-powered platform that figures out who among a large, diverse group of people is the right match to help you, even if you'd never think to ask them. It was tested across universities in 13 countries with real students finding each other for support. Think of it as a smart matchmaking engine, but instead of dating, it connects people whose different experiences make them perfect to solve each other's problems.

By the numbers

consortium partners

countries represented in consortium

EUR 6,587,158

EU funding received

total project deliverables

v4.0

final platform release version

The business problem

What needed solving

Companies with diverse, distributed teams waste enormous potential because people don't know who in their organization has the right complementary skills or perspective. Standard directories and org charts fail because they don't capture the real-world behavioral patterns and cultural nuances that determine whether two people will actually work well together. This leads to repeated problem-solving, underused expertise, and missed innovation opportunities.

The solution

What was built

The project delivered a complete AI platform (v4.0 final release) with diversity-aware matching algorithms, user profiling based on behavior and interactions, a communication alignment mechanism for cross-cultural understanding, and an incentive system to motivate participation. A companion research infrastructure (v4.0) was also built for managing datasets. In total, 33 deliverables were completed.

Audience

Who needs this

Multinational corporations with distributed R&D teams needing better cross-office collaborationEdTech platforms looking to improve peer learning and student matching at scaleInnovation consultancies assembling diverse project teams for creative problem-solvingHealthcare networks connecting specialists across disciplines for collaborative diagnosisProfessional communities and associations wanting smarter member-to-member matching

Business applications

Who can put this to work

Corporate HR & Talent Management

enterprise

Target: Large enterprises with distributed, multicultural teams

If you are an HR director at a multinational company dealing with siloed teams that fail to leverage internal expertise across offices — this project developed an AI matching platform tested across 13 countries that profiles people based on their actual skills and cultural background, then connects them to the right colleague for peer support or knowledge exchange. The platform reached version 4.0 with 33 deliverables completed over 4.5 years of development.

EdTech & Online Learning

any

Target: Online education platforms and university networks

If you are an EdTech company struggling with student engagement and peer learning at scale — this project built a diversity-aware matching engine specifically tested in university settings worldwide. The WeNet platform v4.0 connects students who complement each other's strengths, improving quality of life inside and outside academic environments. With 15 partners across 13 countries, it was validated in genuinely diverse populations.

Creative & Professional Services

mid-size

Target: Innovation consultancies, design agencies, and co-creation platforms

If you run a creative agency or innovation consultancy where assembling the right mix of perspectives is critical — this project developed AI models that learn diversity profiles from people's past behavior and interactions, then match complementary individuals. The platform includes incentive mechanisms to motivate participation and alignment tools that reduce communication barriers across cultural differences.

Frequently asked

Quick answers

What would it cost to license or deploy this technology?

The project received EUR 6,587,158 in EU funding as a Research and Innovation Action. Licensing terms are not publicly specified. You would need to contact the coordinator at Università degli Studi di Trento to discuss commercial licensing or partnership arrangements.

Can this scale to thousands or millions of users in a corporate or platform setting?

The platform reached version 4.0 and was tested across universities in 13 countries, which suggests it handles geographically distributed, multilingual user bases. However, enterprise-scale deployment with millions of users would likely require further engineering. The research infrastructure v4.0 was built for managing large datasets.

Who owns the IP and how can a company access it?

The project was coordinated by Università degli Studi di Trento (Italy) with 15 consortium partners. IP ownership typically follows Horizon 2020 rules where each partner owns what they created. A commercial license would need to be negotiated with the relevant consortium members.

How does this differ from existing team-matching or collaboration tools?

Unlike standard skills-matching tools, WeNet's AI builds diversity profiles from actual behavior and past interactions, not just self-reported skills. It includes a communication alignment mechanism that helps people from different cultural backgrounds understand each other correctly, plus incentive systems to keep people engaged.

Was this tested with real users or just in a lab?

The platform was tested with real student populations at universities across 13 countries spanning Europe, Asia, and the Americas. These were genuine diversity studies with students from different cultural backgrounds, not simulated environments. The final platform release (v4.0) incorporated learnings from these multi-country trials.

What industries beyond education could use this?

The project objective explicitly mentions creative industries and medical diagnosis as areas that benefit from collaborative, diversity-driven approaches. Any industry where bringing together people with complementary expertise improves outcomes — consulting, R&D teams, customer support networks — could apply the matching technology.

Consortium

Who built it

The WeNet consortium brings together 15 partners from 13 countries — an unusually global spread that includes not just European nations but also China, India, Mongolia, Mexico, and Paraguay. Universities dominate with 9 partners (60%), supported by 3 research organizations and 3 industry partners (20% industry ratio). Only 2 partners are SMEs. The consortium is heavy on academic expertise and geographic diversity, which makes sense for a project studying human diversity — but the low industry presence means commercial exploitation will depend on post-project partnerships. The coordinator, Università degli Studi di Trento, is a strong Italian research university with experience in AI and social computing.

UNIVERSITA DEGLI STUDI DI TRENTOCoordinator · IT
JILIN UNIVERSITYparticipant · CN
U-HOPPER SRLparticipant · IT
LONDON SCHOOL OF ECONOMICS AND POLITICAL SCIENCEparticipant · UK
BEN-GURION UNIVERSITY OF THE NEGEVparticipant · IL
AGENCIA ESTATAL CONSEJO SUPERIOR DE INVESTIGACIONES CIENTIFICASparticipant · ES
FONDATION DE L'INSTITUT DE RECHERCHE IDIAPparticipant · CH
EBERHARD KARLS UNIVERSITAET TUEBINGENparticipant · DE
ANOIKTO PANEPISTIMIO KYPROU (OPEN UNIVERSITY OF CYPRUS)participant · CY
AALBORG UNIVERSITETparticipant · DK
MARTEL GMBHparticipant · CH

How to reach the team

Reach out to Università degli Studi di Trento (Italy) — the coordinating institution. SciTransfer can help identify the right contact person.

Order a report on this consortium See UNIVERSITA DEGLI STUDI DI TRENTO profile →

Next steps

Talk to the team behind this work.

Want to explore how WeNet's diversity-matching AI could work in your organization? SciTransfer can arrange an introduction to the research team and help assess fit for your use case.

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