import { Container } from '../../components/Container' import { Eyebrow, SectionHeader, P } from '../../components/Texts' const primaryUseCases = [ { title: 'AI / ML Training', bullets: [ 'Deterministic training pipelines for reproducible experiments.', 'Cryptographically verified model artifacts end-to-end.', 'Autonomous scaling for distributed training runs.', 'Zero-drift environments that remain consistent over time.', ], }, { title: 'Application Hosting', bullets: [ 'Transparent deployments with verifiable execution.', 'Auto-scaling that allocates resources on demand.', 'Instant global distribution across the ThreeFold Grid.', 'Cryptographically secured runtime environments.', ], }, { title: 'Data Processing', bullets: [ 'Deterministic pipelines that document every transformation.', 'Secure computation with cryptographic verification.', 'Auto-scaling resources for fluctuating workloads.', 'Global processing placement to minimize latency.', ], }, { title: 'Scientific Computing', bullets: [ 'Reproducible research environments for shared experiments.', 'Secure workloads with verifiable execution paths.', 'Dynamic scaling for compute-intensive tasks.', 'Global collaboration with sovereign resource control.', ], }, ] const computeSpecific = [ { title: 'Deterministic Training Environments', bullets: [ 'Reproducible ML experiments with identical conditions every run.', 'Verifiable computational research for scientific collaboration.', 'Auditable financial modelling workflows with traceable outputs.', 'Consistent IoT edge processing with predictable performance.', ], }, { title: 'Multi-Platform Application Hosting', bullets: [ 'Kubernetes orchestration with deterministic deployment pipelines.', 'Virtual machines launched with hardware-attested secure boot.', 'Native Linux workloads with cryptographic assurance.', 'Hybrid topologies mixing containers, VMs, and bare metal.', ], }, { title: 'Auto-Scaling Workloads', bullets: [ 'Demand-based scaling that reacts instantly to load.', 'Global distribution across the ThreeFold Grid.', 'Automated failover that restores services without intervention.', 'Cost optimization through intelligent resource allocation.', ], }, ] export function ComputeUseCases() { return (
Use Cases Purpose-built for reproducibility, security, and scale.

From sovereign AI training loops to globally distributed applications, Mycelium Compute keeps environments verifiable and self-orchestrating so teams can focus on building.

{primaryUseCases.map((useCase) => (

{useCase.title}

    {useCase.bullets.map((bullet) => (
  • {bullet}
  • ))}
))}
{computeSpecific.map((useCase) => (

{useCase.title}

    {useCase.bullets.map((bullet) => (
  • {bullet}
  • ))}
))}
) }