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SHEET 01InfrastructureDEF

What is AI Gateway?

An AI gateway is a centralized routing and management layer that sits between AI consumers (users, applications, agents) and AI model providers. It handles request routing, load balancing, rate limiting, authentication, cost tracking, and policy enforcement across all AI model interactions.

SHEET 02UnderstandingNOTES

Understanding AI Gateway

As organizations use multiple AI models from different providers (OpenAI, Anthropic, Google, open-source models), managing these integrations becomes complex. Each provider has different APIs, authentication methods, pricing models, and rate limits. An AI gateway provides a single, consistent interface for all model interactions.

The gateway abstracts provider differences behind a unified API, enabling applications to switch between models without code changes. It enforces organizational policies (spending limits, content filters, usage quotas), provides centralized logging and analytics, and enables intelligent routing that selects the optimal model for each request based on capability, cost, and availability.

AI gateways are essential for enterprise AI governance because they provide a single control point for all AI model usage. Without a gateway, individual teams may independently integrate with different model providers, creating security gaps, compliance blind spots, and uncontrolled spending.

SHEET 03ImplementationBUILD

How assistents.ai implements AI Gateway

assistents.ai's AI Gateway provides a unified control plane for all model interactions across the platform. It supports routing to multiple model providers — including hosted models, self-hosted open-source models, and assistents.ai's own models — through a single consistent interface.

The gateway enforces spending controls, usage quotas, content policies, and access permissions. It provides detailed analytics on model usage, cost, performance, and quality across all consumers. Intelligent routing can automatically select the optimal model for each request based on configurable criteria.

For on-premise deployments, the AI Gateway routes exclusively to locally hosted models, ensuring no data leaves the organization's infrastructure while maintaining the same management capabilities.

SHEET 04Key FeaturesCAP-01..06

Key features of AI Gateway

CAP-01Active

Unified API across multiple AI model providers

CAP-02Active

Intelligent model routing based on capability and cost

CAP-03Active

Centralized spending controls and usage quotas

CAP-04Active

Content policy enforcement at the gateway level

CAP-05Active

Detailed usage analytics and cost tracking

CAP-06Active

Support for cloud, on-premise, and hybrid model hosting

SHEET 05BenefitsOUTCOMES

Benefits of AI Gateway

  • Manage all AI model usage through a single control point

  • Optimize costs with intelligent model routing

  • Prevent uncontrolled AI spending across departments

  • Enable model switching without application changes

  • Enforce consistent security and content policies

  • Gain complete visibility into organizational AI usage

SHEET 06Specification NotesFAQ

Frequently asked questions

What is an AI gateway?

An AI gateway is a centralized management layer for all AI model interactions. It routes requests to appropriate models, enforces policies (spending limits, content filters, access controls), provides usage analytics, and abstracts provider differences behind a unified API. Think of it as an API gateway specifically designed for AI model management.

Why do enterprises need an AI gateway?

Without an AI gateway, AI model usage is fragmented across teams and applications, creating security blind spots, uncontrolled spending, inconsistent policies, and vendor lock-in. An AI gateway centralizes control, providing visibility and governance over all AI model interactions while enabling teams to use the best model for each task.

How does an AI gateway differ from a regular API gateway?

AI gateways add AI-specific capabilities: model routing based on capability matching, token-based cost tracking, content policy enforcement, prompt/response logging for compliance, model performance monitoring, and intelligent fallback when a model is unavailable. Regular API gateways handle routing and rate limiting but lack these AI-specific management features.

Can an AI gateway reduce AI costs?

Yes. AI gateways reduce costs through intelligent routing (sending simple queries to cheaper models), caching (serving identical responses from cache), usage quotas (preventing runaway spending), and analytics (identifying optimization opportunities). Organizations typically see 20-40% cost reduction after implementing an AI gateway compared to unmanaged model usage.

SHEET 08Sign-offREADY

See AI Gateway in action

Schedule a personalized demo to see how assistents’s platform delivers ai gateway for your organization.

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AI Gateway
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Infrastructure
Glossary
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