Get Demo

FL-Dating

Find Your Perfect Match for Collaborative and Federated Machine Learning

The biggest challenge in Collaborative
and Federated Machine Learning?
Finding the right partners!

Introducing FL-Dating - a new way to match ML practitioners!
Think of it as matchmaking for Collaborative and Federated Machine Learning and:

Find teams & researchers with
data structures similar to yours

Use any FL tools
of your choice

Onboard and invite
friends here

Using a dating metaphor, Guardora allows teams to connect for free by posting anonymous listings with details about their available data structures for collaboration. 

Please help us determine the data structure that works best for you.

For reference, you can check how other researchers, ML teams, and collaboration-friendly companies have structured their listings. To check if you already have a match, please use the "Filter" feature on the left.

As you can see, many professionals have already posted their announcements and continue expanding their network—matches are highlighted with red circles.2

What happens after you post your announcement?

Guardora will match you with potential partners who share the same data structure as you. You'll have ample time to review the details before committing. We’re confident that we can help you find mutually beneficial collaboration opportunities.

Once we identify your matches, Guardora will create exclusive channels for you in the Discord Community. From there, it's up to you and your matches—whether it’s a simple introduction, exchanging ideas, or launching joint projects (from small pet projects and proofs of concept to large-scale collaborations).

You’re free to use any available tools that best suit your collaboration. If Guardora has something relevant to offer, we’ll let you know—always with no obligations.

This opportunity is particularly valuable for researchers, ML teams, and companies working with:

  • Federated ML
  • Collaborative ML
  • Distributed ML
  • Split Learning
  • Swarm Learning
  • Gossip Learning
  • Edge Learning
  • Decentralized ML
  • Blockchain for ML
  • Asynchronous ML
  • Peer-to-Peer ML
  • Knowledge Distillation for Privacy
  • Homomorphic Encryption for ML
  • Differential Privacy for ML
  • Secure Multi-Party Computations for ML
  • Zero-Knowledge Proofs for ML
  • Privacy-Preserving Generative Models
  • Secure Aggregation for FL
  • Oblivious Transfer for ML
  • Trusted Execution Environments for ML

Didn’t find a perfect match yet?

Good news: that means you have the chance to be the first! Keep in mind that there may be more than one potential match.

Let’s create your first listing. Click the + ADD NEW button, drag and drop your options, and submit the form.