Tessryn is being built for AI agents and distributed inference. Its kernel, native drivers and cluster services are designed together so qualified machines can share the work.
Development is open today. Running the operating system comes after the boot, hardware and release gates.
On your server
Target hardware / Qualification first
The first targets are exact x86-64 UEFI profiles with native networking, NVMe storage and one selected NVIDIA family. Installable images will follow the roadmap’s release gates.
Use your Mac to explore the design, edit the source and run the checks above. Native Apple M5 boot, GPU and transport support have separate qualification gates.
A native macOS installer or worker app is not available.
The intended hosted service will provide a console for creating clusters, enrolling qualified machines and placing models. The operating system remains an independent open-source project.
Provisioning, enrollment and native APIs still need implementation and qualification.
The plan is a managed experience in the spirit of EKS or DigitalOcean: create a cluster, connect qualified machines and deploy a model.
A hosted management service will handle the setup. Tessryn will run on the workers.
Proposed workflow · Not available yet
01
Create a cluster.
Select a qualified profile and an explicit resource budget.
02
Connect machines.
Boot Tessryn and authenticate enrollment of eligible workers.
03
Place a model.
Verify artifacts, reserve memory and distribute resident shards.
04
Use the cluster.
Submit inference requests and bounded agent tasks through native APIs.
The public OS’s first product proof is a four-machine cluster, including a qualified wired laptop, executing one model larger than any individual worker can hold.