Access
Unified model endpoint
Provide a consistent calling endpoint, authentication method and model naming structure across protocols and suppliers.
Platform capabilities
From model access to enterprise governance, build a complete AI operations layer.
Data Future AI Gateway brings model access into a unified system for permissions, audit, cost, reliability and delivery management.
Keys
API keys and groups
Separate keys and permissions by team, project, environment and business line with quota and policy controls.
Route
Model routing policies
Manage models, channels, groups and fallback paths based on enterprise policies and workload needs.
Audit
Usage and cost audit
Capture requests, tokens, error codes, estimated cost and balance changes for reporting and budget control.
Health
Channel availability
Run health checks and observe availability, latency and abnormal status for faster troubleshooting.
Risk
Security and risk controls
Combine account security, access control, abnormal request visibility and approval workflows to reduce production risk.
Capability matrix
A shared foundation for engineering, business and platform teams.
| Capability | Problem solved | Enterprise value |
|---|---|---|
| Unified access | Complex integration across models, protocols and clients | Reduce repeated adaptation and migration cost |
| Permission governance | Scattered keys, unclear project boundaries and access drift | Manage AI access by organization and business line |
| Usage audit | Invisible cost, hard-to-control budget and unclear abnormal usage | Support internal reporting, chargeback and compliance audit |
| Reliability monitoring | Single channel failures impacting production systems | Provide status visibility, fallback paths and troubleshooting evidence |
| Service delivery | Procurement, contract and technical support processes are missing | Support long-term ToB cooperation and managed service |
Use targets
Adapt to different enterprise AI usage patterns.
The platform can act as the access, governance and observability layer from a single AI application to a company-wide model foundation.
Developer toolsIDE plugins, agents, coding assistants and automation tasks.
Business systemsCustomer service, knowledge bases, content generation and data assistants.
Platform servicesInternal AI gateways, SaaS multi-tenant model services and unified billing.
Private modelsEnterprise-built models, vertical models and third-party model suppliers.