Enterprise Application AI Access
Pain Points
Pain Points
Traditional Applications are Difficult to Directly Connect to AI
Most existing enterprise business systems provide capabilities via Web, API, database, or messaging interfaces, lacking standard access methods oriented toward AI Agents or the MCP ecosystem. Thus, enterprise capabilities cannot be directly invoked by models and intelligent agents.
Scattered Interfaces and Inconsistent Access Methods
Enterprises often have numerous legacy systems, custom systems, and services on different technology stacks. Inconsistent interface standards, incomplete documentation, and decentralized governance increase the difficulty of AI access and subsequent operations management.
Complex Permission Boundaries and High Security Risks
When enterprise application capabilities are opened to AI models, intelligent assistants, or Agents, controlling "who can call which tools, access which data, and perform which operations" becomes a critical issue in AI deployment.
Lack of Unified Governance and Continuous Operations Capabilities
If AI applications connect directly to individual business systems, it not only creates a complex integration link but also easily forms new system silos, leading to uncontrollable access, unauditable calls, unmanageable costs, and untraceable risks.
Solution Overview
No.1 API to MCP Tools Conversion
Supports converting enterprise existing REST APIs, HTTP services, and business interfaces into standardized MCP Tools, lowering the technical threshold for traditional applications to join the AI ecosystem and protecting existing system investments.
No.2 Unified Proxy and Management of MCP Services
Supports unified proxy, registration, publishing, and governance for MCP Servers, Tools, and invocation links, helping enterprises build a standardized AI tool access system.
No.3 Unified Permission Control and Access Management
Supports fine-grained control over users, applications, intelligent agents, tools, service scopes, and operational permissions, ensuring different subjects access corresponding capabilities strictly within their authorized limits across various scenarios.
No.4 Unified Access and Security Governance for AI Services
Supports unified access for public cloud models, privatized models, and third-party AI services used by the enterprise. Combined with data privacy protection, auditing, and policy control capabilities, it elevates security and compliance during AI usage.
No.1 API to MCP Tools Conversion
Supports converting enterprise existing REST APIs, HTTP services, and business interfaces into standardized MCP Tools, lowering the technical threshold for traditional applications to join the AI ecosystem and protecting existing system investments.
No.2 Unified Proxy and Management of MCP Services
Supports unified proxy, registration, publishing, and governance for MCP Servers, Tools, and invocation links, helping enterprises build a standardized AI tool access system.
No.3 Unified Permission Control and Access Management
Supports fine-grained control over users, applications, intelligent agents, tools, service scopes, and operational permissions, ensuring different subjects access corresponding capabilities strictly within their authorized limits across various scenarios.
Business Values
● Significantly Reduce Costs: Through high-frequency semantic caching at the gateway layer and fine-grained (department/Agent-based) quota scheduling, it effectively intercepts invalid redundant calls, substantially cutting large model Token inference costs and API procurement expenses.
● Exponential Efficiency Boost: Relational authorization (ReBAC) enables permissions to automatically follow organizational structure inheritance, significantly reducing tedious manual authorization and auditing workloads, while compressing the cycle for business personnel to gain data insights from hours to seconds.
● Zero-Vulnerability Security: The SPIFFE keyless architecture combined with millisecond-level network-wide blocking of anomalies builds an impeccable line of trust defense, eliminating massive regulatory fines triggered by unauthorized scraping and non-compliant data synchronization.
● 100% Holographic Compliance: Achieves 100% audit traceability and decision explainability across the entire lifecycle—from the user's initial intent input to complex node task distribution—clearing compliance blind spots for large-scale enterprise AI deployment.
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