When you run AI workloads on someone else’s hardware, trust matters. Your prompts, your data, your outputs flow through systems you do not control. The same is true the other way: if you share your GPUs, you are letting strangers run code on your machines.
We could have launched with open registration. More providers, more customers, faster growth. But we chose a different path.
Verified organizations first
Coranor starts with verified organizations: schools, research labs, companies. Not because individuals are bad, but because organizations are easier to verify and hold accountable.
When a university offers GPU time, we know who they are. We can verify their identity, check their track record, and establish a relationship. If something goes wrong, there is a clear entity to work with.
Building trust takes time
Trust is not a feature you ship. It is earned over time through consistent behavior. By starting with verified organizations, we:
- Reduce risk for early customers
- Create a foundation of reliable providers
- Learn what works before scaling
- Build reputation we can extend to others later
What this means for you
If you are a customer, you get peace of mind. The GPUs running your workloads belong to real organizations with reputations to protect.
If you want to provide GPUs as an individual, we hear you. Our long-term vision includes a broader network. But we need to get the fundamentals right first. Security, reliability, trust.
The path forward
We are not building Coranor in a hurry. We are building it to last.
Starting small with verified organizations lets us focus on what matters: making the platform work well for everyone who uses it. As we prove the model and build trust, we will expand.
If you are part of an organization with underused GPUs, we would love to talk. If you are an individual, stay tuned. We will get there.