Custom AI Endpoint Support

Take total control of your conversational AI diagramming workspace. Connect your organization’s approved AI infrastructure to route chatbot requests through your preferred providers, maintain strict data governance, and optimize response quality.

Why Configure a Custom AI Endpoint?

Visual Paradigm includes robust default AI capabilities out of the box, but organizations often need granular oversight, stricter data protection, and direct control over their provider infrastructure.

Enterprise Data Governance

Ensure all AI requests strictly follow your company's approved security standards, compliance frameworks, and internal data residency rules.

Strategic Model Selection

Deploy high-throughput models for fast diagram creation, or utilize deep-reasoning models for multi-layer architecture generation and code fixes.

Cost & Usage Optimization

Apply your own corporate API keys to take advantage of enterprise pricing, manage custom token limits, and centralize spend monitoring.

Optimized Latency & Performance

Choose region-specific providers and localized endpoints to minimize network hops, eliminate cross-border delay, and boost throughput for distributed teams.

Key Benefits for Your Workspace

Empower IT managers, solution architects, and security officers with total oversight over organizational AI usage.

Enterprise Security & Governance

Route team requests through approved AI vendors and accounts that strictly adhere to your corporate IT policies and regulatory compliance guidelines.

Complete Infrastructure Control

Maintain direct vendor relationships, utilize organization-managed API keys, and enforce customized usage quotas across all workspace projects.

Tailored Model Flexibility

Choose specific AI engines to optimize for reasoning depth, output quality, generation speed, or specialized multi-language processing.

Operational Consistency

Establish a single endpoint configuration centrally to guarantee a standardized AI experience for every team member in the workspace.

Regional Performance Optimization

Reduce response latency and improve uptime by selecting geographically local endpoints tailored to your distributed workforce.

Direct Cost & Budget Management

Consolidate billing within your existing vendor accounts and apply enterprise tier discounts directly to workspace usage.

How to Configure Your Custom Endpoint

Easy central configuration deployed directly by your Workspace Manager for the entire team.

Step 1

Enter Provider & Credentials

Navigate to the LLM Configuration page, select your approved AI Provider, paste your organization’s API Key, and specify the target Model ID.

Step 2

Fine-Tune Model Behavior

Adjust operational parameters to fit your needs. Configure Max output tokens for longer outputs or set Reasoning effort / Thinking mode where supported.

OpenAI

Anthropic

Google

DeepSeek

Mistral

Groq

Qwen

Cohere

+More

Step 3

Enable Routing & Save

Toggle on Route requests through this configuration and click Save changes. Your custom setup immediately applies to all eligible workspace users.

Model Performance Benchmarks

Our engineering team conducted internal performance tests under standardized workloads to help you choose the right model for your workspace needs.

Fast Response

High-Speed Models

Delivered rapid generation times while maintaining strong output quality for interactive diagramming workflows:

Deep Response

High-Reasoning Models

Exhibited longer generation latency during testing due to deeper reasoning steps, extended chain-of-thought, or complex model architecture:

Prerequisites & Administration

Require Self-Hosted or Private LLM Deployment?

If your organization requires internally hosted models, dedicated on-premises infrastructure, or custom endpoint integrations for unlisted tools, our Enterprise Solutions Team can build a customized support plan.

Contact Enterprise Support