Enterprise AI Infrastructure Platform
Unify multi-cloud model access, token cost, permissions, and audit so enterprise AI can run in production.
XmindAI Control Plane
Azure
AWS
GCP
Oracle
DeepSeek
Qwen
GLM
火山引擎
Three Core Platforms, Two Delivery Capabilities
Token governance, agents, AI coding, plus app generation and FDE-led rollout services.
Token Governance Platform
Govern enterprise model calls, token usage, access, cost, and billing.
Enterprise Agent Platform
AI Coding Platform
An AI coding and engineering productivity platform for enterprise delivery workflows.
AI App Builder
Describe pages, data, and key actions in a few sentences, then generate a first project version for preview and iteration.
FDE Delivery Service
A delivery engineer leads discovery, integration, governance, and enablement for enterprise AI rollout.
One Enterprise AI Control Plane from Access to Delivery
Bring developer access, governance, service assurance, and delivery into one platform view.
Developer Access
Use APIs, SDKs, keys, consoles, and docs to onboard engineering teams.
Governance Ops
Manage tokens, budgets, access, logs, audit, and reconciliation together.
Service Assurance
Protect key calls with routing, throttling, failover, monitoring, and tickets.
Business Delivery
Move agents, AI coding, assistants, and app generation into real workflows.
Cloud Access and Partner Coverage
Keep choice across cloud supply, model access, and partnership paths instead of relying on one vendor.
Use Azure OpenAI, AWS Bedrock, Google Vertex AI, and other ecosystems while keeping stability, cost, and deployment options in your control.
Best suited for secure, governed, enterprise-scale operations.
Designed for high availability, concurrency, and cross-region workloads.
Strong fit for data-intensive, AI-native, and multimodal scenarios.
Well suited for China-region deployments, elastic compute planning, and enterprise application delivery.
Microsoft
Microsoft cloud ecosystem collaboration
Built for enterprise AI infrastructure discussions and delivery paths in the Microsoft cloud ecosystem.
Oracle
Oracle cloud ecosystem collaboration
Available for Oracle infrastructure and mission-critical industry solution discussions.
Designed for Core Industries and Fast AI Deployment
Apply the platform to service, knowledge, engineering, content, and process workflows.
Gaming
Ecommerce
Education
Financial Services
Manufacturing
Software and Internet
Production AI Architecture Layers
Separate supply, access, governance, execution, and delivery so the platform can evolve over time.
Cloud and Model Supply Layer
Developer Access Layer
Model Gateway Layer
Token Governance Layer
Intelligent Execution Layer
Application Delivery Layer
Enterprise Service Layer
Start with AI infrastructure
Review access architecture, governance boundaries, and first rollout scenarios.