turn the intelligence you rent
into capability you own.
The capability you build into a rented model stays the vendor's, not yours. Caletta turns that around with a loop you own: routing sends each call to a frontier API or a model on your own silicon, capture turns your usage into a training set you keep, and training runs on hardware you hold. The security layer (policy, brokered secrets, routed egress, operator-owned evidence) keeps that loop on your side of the line.
owned runtime
route · distill · train · keep control
Learned model routing and corpus capture in llm-router, and distributed training over the mesh that turns your usage into a model you own. Routing and capture are built; the distillation and training that close the loop are in build.
A pure-Go MLX runtime for capable local inference and training, with Metal tracing. The mesh transport ships as mlx-go-iroh; the distributed-training datapath is built and publication-pending. The long arc: democratized distributed training on hardware people already own.
cgo-free Apple bindings, static Go binaries, and clear trust boundaries.