Business · AI Products

Every AI Call in the Enterprise,
Controlled Through One Gateway

AURDA AI Gateway is the single gateway that every public and private model, MCP, and AI Agent call passes through. Access rights, quotas, budgets, and AI safety policies are controlled centrally; routing and failover keep services stable; tokens, requests, and traces are observed in one place. It is a standalone product with no dependency on an existing platform: combine it with AURDA AI Infra as a Suite, or deploy it on its own.

Connect · Control · Route · ObserveThe four jobs an enterprise AI service needs, handled by one gateway
StandaloneBuilt and deployed on its own, with no dependency on an existing platform
AI FinOpsUnified analysis of AI usage and cost, reported weekly, monthly, and yearly

Why

The Wider AI Use Spreads, the Harder It Is to Manage

As components grow beyond models to MCP and Agents, and as the parties using them multiply, a consistent system of control and operations becomes necessary. Regulation brings that moment forward.

01

Expanding AI use

Who uses AIAI componentsOrganizationsUsersServicesAgentsLLMMCPAI Agent
A Growing Ecosystem and More Users

Components multiply fast, from LLMs to MCP and AI Agents, and the parties using AI diversify across organizations, users, services, and Agents.

Increasingly Complex Control Policies

Policy demands grow, from controlling AI access and usage to managing sensitive data.

Limited Operational Visibility

Scattered AI usage and request flows are hard to see as a whole.

02

Regulatory compliance

Law
AI Basic Act in Force (Jan 2026)

Korea's AI Basic Act imposes risk management, monitoring, and record-keeping duties for high-impact AI. Control and logging systems need to be in place within the grace period.

  • Risk management
  • Monitoring
  • Record-keeping
Public sector
National Network Security Framework (N2SF)

Generative AI use in the public sector now requires usage logs and access control. Tiered access control is the means of meeting the requirement.

  • Usage logs
  • Access control
Finance
Easing of Financial Network Separation

As external LLM adoption opens up, control over mixed external and internal models, usage records, and internal audit demands follow.

  • Mixed-model control
  • Usage records
  • Internal audit

Concept

The One Gateway Every AI Call Passes Through

Calls from users, business services, and AI applications pass through AI Gateway to public and private models, MCP servers, and AI Agents. Callers only need the gateway address, and a model swap behind it changes nothing for them.

AURDA AI Gateway concept: calls from users, applications, and AI Agents pass through AI Gateway to public and private models, AI services, and enterprise systems
ConnectUnified endpoint
ControlAccess · Budget · Policy
RouteBalance · Failover · Canary
ObserveToken · Request · Trace

Console

From Connection to Observation, in One Console

These are the product screens as they are. Model and MCP connections, access profiles, guardrails, routing, and usage are all operated from one console.

AI Gateway overview dashboard: cumulative requests, token usage, average latency, estimated cost, and the 24-hour trend

Dashboard

The Whole Gateway on One Screen

Requests, token usage, average latency, and estimated cost are shown as a monthly total and for today. Hourly request and token trends sit alongside the routing strategy distribution.

Architecture

What One Gateway Does, in Pictures

Where calls come from, where they go, and what AI Gateway controls and distributes in between.

RequestAuth · AccessRBAC · API keyQuota · BudgetOrg → Team → ServiceGuardrailsI/O security policyHITL approvalHigh-risk onlyModel · MCP · AgentBlocked · RejectedEvery step is recordedUsage and approval logs become the evidence for AI Basic Act and N2SF compliance

Control Pipeline

Four Checks Between a Request and the Model

Authentication and access, quota and budget, guardrails, and human approval for high-risk requests, in that order. Requests that fail are blocked or rejected. Every step is recorded, which becomes the evidence for AI Basic Act and N2SF compliance.

RequestsIntelligent routerCache · Load · HistoryProduction model A90% of requestsNew model BCanary 10%Fallback pathAuto failoverThen widenHealth checkRepeated questions are answered from cache, cutting inference cost and response time

Routing

Distribute by Cache and Load, Roll Out New Models Gradually

Repeated questions are answered from cache, and requests are distributed by load and processing history. A new model takes a share of requests first (canary), is validated, then widened. On an outage, traffic fails over to an alternate path automatically.

Key Features

Connect, Control, Route, Observe: One Gateway

Models, MCP, and Agents connect through one gateway, and policies, routing, and usage are managed centrally.

01
Connect
Unified Endpoint Management

Public and private models, MCP servers, and AI Agents connect through a single gateway endpoint. One standard API links existing AI services quickly, and swapping a model behind it leaves the caller untouched.

Standard and Non-Standard AI APIs

From standard protocols to OCR and newly released APIs, services attach flexibly in passthrough or custom mode. Manufacturing equipment and system protocols connect through an add-on.

MCP Repository

MCP servers are registered, deployed, and versioned here. Access rights and call control for registered MCP servers are handled in the same place.

02
Control
Profiles, API Keys, and Access Rights

Profiles and API keys are issued per user, organization, and service, and role-based access control (RBAC) decides which models and tools each may reach.

Quotas and Tiered Budgets

Usage is measured in each model's own units, whether tokens, pages, or requests, and budgets are allocated and capped by organization, team, and service.

Guardrails and HITL Approval

AI safety policies apply consistently to inputs and outputs, and high-risk requests run only after a person approves them. Approval and rejection history is retained as audit evidence.

03
Route
Intelligent Routing

Requests are distributed according to processing history and load. The same question is not processed from scratch every time.

Backend Distribution, Health, Failover

Requests spread across multiple backends whose health is checked continuously, and traffic fails over to an alternate path on an outage.

Canary Model Switching

A new model is rolled out to a share of requests first, checked, and then widened. Model replacement risk stays minimal.

04
Observe
Gateway and Model Monitoring

Throughput, latency, and errors per gateway and per model, on one screen.

Token and Request Tracing

Token usage and a trace per request show where time goes, from queueing to generation.

AI FinOps Reporting

AI usage and cost are analyzed together and reported on the enterprise's own cycle, weekly, monthly, or yearly.

Editions

Pick the Level of Control You Need

Standard covers connection and access control. Enterprise adds tiered budgets, guardrails, and HITL. The manufacturing protocol comes as an add-on.

Edition

Standard

The starting point for organizations that need model connection and access control.

  • Unified endpoint management
  • Authentication and authorization (RBAC)
  • Token quotas
Edition

Enterprise

For organizations running AI across departments with audit obligations.

  • Everything in Standard
  • Budget control by organization, team, and service tier
  • Guardrails and unified security
  • HITL approval
Add-on

Manufacturing Protocol Add-on

Brings shop-floor data and AI calls under the same control. It can be added to either edition.

  • Manufacturing equipment and system protocol connection

Positioning

A Complement to Security Products, Not a Competitor

Data-leak prevention stays with security products. Model connection, access control, and budget control belong to AI Gateway: an AI-specific, standalone gateway that runs inside your network.

Role comparison of AURDA AI Gateway against Korean AI security gateways, open source gateways, and global API management platforms
FeatureKorean AI security gatewaysOpen source gatewaysGlobal API management platformsAURDA AI Gateway
Core roleData-leak prevention (DLP)Model call proxy and routingAn add-on to API managementSingle gateway and usage control for models, MCP, and Agents
GovernanceInput and output security policiesBasic key and limit managementAssembled from pluginsRBAC, tiered budgets, guardrails, HITL
Cost controlOut of scopeBasic usage aggregationPer-request billing managementToken budgets by organization, team, and service
Deployment and supportOn-premise, Korean supportSelf-built, self-operatedGlobal pricing and supportIn-network deployment, commercial support, audit response

Qualitative comparison based on our products, October 2026Security products block data leaks; AI Gateway controls model connection, access, and budgets. The two work together as complements.

AURDA Suite

One System, from Resources to Usage Control

AURDA Suite · Deploy separately or togetherAURDA AI InfraResources · ServingGPU · NPU management · partitioningKubernetes managementModel servingAgent servingUnified monitoringAURDA AI GatewayAccess · ControlUnified endpoint managementAuthentication · AuthorizationToken quota · Tiered budgetsGuardrails · HITL approvalMCP Repository · Access control

AI Infra + AI Gateway

AI Infra Runs Resources and Serving; AI Gateway Runs Access and Control

AURDA AI Infra runs GPU and NPU resources and model and Agent serving. AURDA AI Gateway handles access, control, and integration. MCP servers are registered, deployed, and versioned in AI Gateway, which also controls their access rights and calls. Deploy them separately or together; AI Gateway also runs on its own in a third-party GPU environment.

This download is a product brochure (PDF). We do not distribute software installers.To see the product in action, please reach us through Contact Sales.

Download

AURDA AI Gateway Product Overview

PDF · 8.8MB · as of 2026.11

Download Brochure

Considering Uracle?

From a product demo to a quote, a consultant will get back to you within one business day.

Contact Sales