Tensorplex Labs builds applications and infrastructure for AI using decentralised technologies, positioning itself against the concentration of AI capability in a handful of large providers. The argument is straightforward: if compute, models and data all sit with three companies, both pricing and access are set by them.
Decentralised approaches attempt to distribute that, coordinating compute and contribution across many participants rather than one datacentre operator. The honest assessment is that this is an active area of experimentation rather than a settled alternative, decentralised training and inference face genuine coordination and latency costs that centralised infrastructure does not.
It is worth understanding as part of the decentralised-AI movement rather than as a drop-in replacement for a cloud provider. Anyone evaluating it should be clear which specific workload they intend to run and compare the economics directly, since the case varies enormously by task.
