Managed Cloud

Launch a unified AI access platform in a shorter cycle.

Managed Cloud is designed for enterprise teams that need rapid multi-model access, lower operational overhead and ongoing technical support.

Lower operations

Hosted environment and updates

Data Future maintains the base environment, platform upgrades and service visibility so your team can focus on business integration.

  • Platform environment initialization
  • Version updates and configuration support
  • Basic service status monitoring
Dedicated setup

Policies configured for your teams

Configure keys, groups and usage policies based on your model scope, team structure, budget metrics and application scenarios.

  • Multi-model access configuration
  • Team and project permission separation
  • Usage statistics and billing rules
Fast launch

Integration, testing and rollout support

Receive documentation, joint testing and launch guidance for SDKs, clients, internal apps and agent workflows.

  • Integration documents and examples
  • Pre-launch testing support
  • Production issue troubleshooting
Best fit

For teams piloting quickly and scaling gradually.

Managed Cloud supports R&D departments, AI application teams, innovation teams and SaaS teams from proof of concept to production usage.

Pilot stageInternal AI applications need unified access and management.
Business launchTeams need a production-grade endpoint, permissions and usage records.
ProcurementContracts, invoicing, technical onboarding and service windows are required.
Future migrationUpgrade to private deployment when data boundary requirements become stricter.
Launch process

Move from requirements to business integration as a project.

Requirement review

Confirm model scope, usage scale, team structure, budget and launch timeline.

Environment setup

Open the managed environment and align base configuration and service boundaries.

Integration testing

Support apps, SDKs, clients or agent workflows to validate model calls.

Production launch

Optimize policies based on usage, errors and feedback, then establish ongoing support.