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Case study · Public AI Compute

AI computesold by the token.

An operator of a large-scale public AI computing service that aggregates fragmented computing resources into a shared, on-demand utility. It gives education, scientific research and enterprise innovation inclusive access to AI computing power, so users consume compute as a service without investing in dedicated infrastructure. As AI adoption spread, computing resources stayed fragmented, underused, and within reach of only a small number of organizations.

Constraints and answers

Idle capacity everywhere, and almost nobody able to buy it.

The platform that puts a student and an enterprise on the same schedule

01

Fragmented capacity left utilization low

Fragmented computing resources limited accessibility and left overall utilization low.

Answer

01

Unified public AI computing resource pool

A cloud-native platform aggregating dispersed computing resources into one public pool, giving shared on-demand access to AI computing power.

02

Upfront cost kept access to a few

High upfront costs restricted AI computing access to a small number of organizations.

Answer

02

Token-based, pay-as-you-go access

A token billing model lets users buy and consume computing power flexibly, which is what actually lowers the entry barrier.

03

Allocation models could not flex with demand

Traditional allocation models could not support flexible, on-demand usage for diverse user groups.

Answer

03

Inclusive AI service delivery

Built for education, scientific research and enterprise AI development, including model training, fine-tuning and data analysis workloads.

04

No affordable route for education and research

Education, research and smaller enterprises lacked affordable access to AI training and inference resources.

Answer

04

Cloud-native scheduling and operations

Centralized scheduling and operational management give efficient allocation, fair distribution and stable service across very different users.

05

Regional capacity idle and disconnected

Regional computing capacity sat idle and disconnected from the wider innovation ecosystem.

Answer

05

Cross-border service orientation

The platform carries regional and cross-border AI computing services, extending access beyond local boundaries.

Billing was the barrier, so billing was the fix.

The results

Fragmented capacity, turned into a public utility.

AI COMPUTING ACCESS
Students, researchers and enterprises gained affordable access to AI compute.
PUBLIC COMPUTING RESOURCE POOL
Fragmented capacity consolidated into a shared, utility-style service.
ENTRY BARRIER TO AI ADOPTION
Token-based pricing enabled flexible, pay-as-you-go consumption.
AI SERVICE COVERAGE
Education, scientific research and enterprise AI development scenarios.

Four outcomes stated in kind, and all of them came from capacity that was already there.

The stack

What was deployed

Computing scheduling, model services and AI workload orchestration, which is what makes public on-demand AI computing possible.

Cloud-native platform services for resource management, observability and multi-tenant operations.

The compute, storage and networking underneath a public AI computing platform that has to stay up.

Nota sobre capacidades

Las capacidades, credenciales y referencias de implementación mostradas en este sitio reflejan el trabajo colectivo del equipo central de ingeniería de Amanah. Ciertos proyectos se entregaron bajo entidades previas o afiliadas. Las implementaciones soberanas son confidenciales por mandato, por lo que no se identifica a clientes individuales. Las referencias subyacentes son verificables bajo NDA.

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