Sabrine Lachheb
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Home / Projects / Labify Connect
Case studies · 2025–26 · research · AI · product concept

Labify Connect

Helping scientists find collaborators they can trust.

Labify Connect grew out of my Master’s thesis, Designing Trust for Scientific Collaboration. It is a platform concept where verified researchers find collaborators, with AI-assisted matching on top of trust signals.

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RoleUX researcher & product designer
Timeline2025–26
TeamSolo, thesis project
ToolsSurveys, interviews, Figma, prototypes

The challenge

Scientists collaborate through personal networks, conferences and email. LinkedIn, ResearchGate and similar platforms lack verification and disciplinary depth, so trust is hard to establish online.

Goal. Create a place where trust, function and scientific needs meet, and where collaboration starts with the right match.

My role

  • Designed and ran the mixed-methods research
  • Defined five design principles from the findings
  • Wrote the SWOT, MVP scope and AI-matching concept
  • Built a clickable prototype: landing, verification, onboarding, matching, profiles, collaboration workspace
Process

How we got there.

1

Research

Survey of 29 researchers and 3 interviews on habits, trust and platform needs.

2

Insights

Trust is the top factor in scientific collaboration (4.73 out of 5).

3

Principles

Five principles: verified identity, transparent contributions, peer endorsement, inclusive interaction, contextual communication.

4

Concept & MVP

Scope, SWOT and an AI-matching approach.

5

Prototype

Verification (ORCID), onboarding, matching and profile screens.

Process in pictures

What it looked like.

StrengthsORCID-based credibility, built for co-creating, resource and funding sharing, multilingual and inclusive.
WeaknessesAdoption in a field slow to switch tools, data privacy and IP, MVP scope, need for institutional partners.
OpportunitiesCross-disciplinary collaboration, AI matchmaking and funding suggestions, university and journal partnerships, EU grant platforms.
ThreatsBig platforms entering the niche, resistance to yet another tool, limited researcher time, proving ROI.
Results

What changed.

29survey responses
3interviews
4.73/5importance of trust
72.7%would use a verified platform

A research-backed concept with clear principles, an MVP scope and a prototype that people can click through.

Design opportunity: AI-based matchmaking and funding suggestions, built on verified identity (ORCID), so recommendations stay credible.

What I learned

AI is only as trusted as the data and identity behind it. Verification came first, and matching second.

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