hosted.ai - 2026 Pricing, Features, Reviews & Alternatives

hosted.ai is a GPU orchestration and AI infrastructure platform for service providers, cloud providers, telecommunications operators, hosting providers, and neocloud operators. It addresses GPU underutilization through software-defined GPU pooling, multi-tenant provisioning, and intelligent scheduling. It is designed for organizations launching or scaling GPU-as-a-Service offerings, lowering capital expenditure barriers for new entrants and enhancing margins for established providers. The platform integrates GPU orchestration with business operations tools and customer-facing portals to provide a unified infrastructure environment.

The platform’s core functionality relies on software-defined GPU technology to enable elastic resource provisioning through pooled GPUs and multi-tenant allocation. Physical GPUs are assigned to pools and workloads access the combined resources rather than fixed slices or dedicated cards. Task isolation and adaptive scheduling distribute workloads according to priority. Configurable GPU overcommit ratios from two to ten permit service providers to offer virtual GPU resources that exceed physical capacity. When video memory limits are reached, system RAM is employed to preserve service continuity. Both shared pools and dedicated GPU configurations are supported to meet diverse workload requirements.

Business operations features include precise control over GPU packaging structures, metering of resource consumption, quota management, and role-based access control with team administration. A self-service portal can be customized to reflect provider branding and enable independent provisioning by end users. An integrated AI model library is available alongside support for bring-your-own-model workflows. Metering data feeds into billing systems and can be accessed through a REST API for seamless integration with WHMCS and other billing engines.

The platform can be deployed as a standalone GPU-as-a-Service layer on existing cloud infrastructure or as a complete hyperconverged stack. Hardware-agnostic design supports a variety of server and GPU models without vendor lock-in. For providers lacking in-house GPU capacity, wholesale GPU resources can be accessed on demand. Deployment involves installing the software, configuring GPU pools with associated packages, launching services via a branded portal or integrated billing system, and scaling by adding GPUs to pools while monitoring utilization and optimizing overcommit ratios. Twenty four by seven support is provided with a fifteen-minute service level agreement.