What Is an AI Gateway? How It Works and Where ShareAI Fits

An AI gateway is the control layer between your application and the AI models you use. Instead of wiring your product separately to each model provider, you send requests through one layer that can route traffic, standardize responses, improve reliability, and give you better visibility into usage.

That matters once an AI feature moves beyond a demo. A single provider integration may be enough at the start. But production traffic usually brings new questions: which model should handle each request, what happens when one route slows down, how do you compare cost and latency, and how do you keep your app from being tied to one provider’s interface?

ShareAI fits this conversation as a people-powered AI marketplace and API. It gives teams one API for 150+ models, plus routing, failover, marketplace visibility, and a Builder layer for monetizing AI traffic from an app you already own.

What is an AI gateway?

An AI gateway is a layer that sits between your app and one or more AI model providers. Your app sends a request once, and the gateway decides how that request should be handled.

• Standardized access to multiple model providers
• Routing requests to the right model
• Retries or fallback when a route fails
• Usage, cost, and performance tracking
• Less work when you add or switch providers later

The simplest way to think about it is this: your app focuses on product logic, while the AI gateway focuses on model access and traffic control.

How an AI gateway works

A user action in your app creates an AI request. That request goes to the gateway first, not directly to one provider.

From there, the gateway can choose a model based on the task, switch providers if latency or availability changes, normalize the response into one predictable format, record token usage and request behavior, and return the result back to your application.

For example, a support product may send every user message through one interface, but use different models depending on the workload. A low-cost route may handle basic classification. A stronger model may handle complex answers. If one path becomes unreliable, traffic can move to a fallback route.

That is the operational value of an AI gateway. It helps teams manage AI traffic as a system instead of as a pile of separate integrations.

What teams expect from an AI gateway

Unified model access

A strong AI gateway gives you one integration instead of separate provider-specific code. That lowers switching cost and makes experimentation easier.

With ShareAI, teams can browse and compare models and start from one API integration.

Routing and failover

Production AI traffic is uneven. Some routes get expensive. Some get slow. Some fail.

A useful AI gateway gives you routing logic and fallback options so your app is less dependent on one provider path. ShareAI’s positioning here is practical: one API, marketplace visibility, and failover when a route degrades.

Usage visibility

AI traffic is hard to manage if you cannot see what is happening. Teams want to understand price, latency, availability, and total usage without stitching together multiple dashboards.

ShareAI’s marketplace framing is useful here because the product is not just a relay. It is designed to expose model and provider signals so routing decisions are more informed.

A cleaner path to scale

An AI gateway does not remove all complexity, but it prevents provider sprawl from taking over the codebase. That becomes more important once multiple teams, products, or customer segments rely on the same AI layer.

AI gateway vs API gateway

An API gateway and an AI gateway are related, but they are not the same thing.

A traditional API gateway manages general application traffic between clients and backend services. An AI gateway is narrower and more AI-specific. It focuses on model traffic, provider selection, fallback behavior, token-aware usage, and AI-oriented observability.

• API gateway: routes general app traffic to services and microservices
• AI gateway: routes AI requests to models and providers
• API gateway: focuses on backend API management
• AI gateway: focuses on model access, reliability, and AI traffic control

Many teams will use both. The API gateway stays in front of the application stack. The AI gateway manages the model layer behind the product’s AI features.

Where ShareAI fits

ShareAI should not be described as only an AI gateway, because that understates the product. It is an AI marketplace and API for customers, Builders, and Providers.

For customers and developers, ShareAI fits the AI gateway role well when the goal is to access many models through one API, compare routes, and reduce provider complexity. You can read the docs, try the Playground, or generate credentials without building a separate abstraction layer first.

For Builders, ShareAI adds something most AI gateway discussions ignore: monetization. If you already own or maintain an app outside ShareAI, you can route AI inference traffic through ShareAI, set a surcharge or margin, let customers pay ShareAI directly for routed usage, and receive monthly payouts based on generated earnings through the Builder Console.

That does not make ShareAI an app builder. The application still lives outside ShareAI. ShareAI handles the routing, usage, billing, and payout layer for the AI traffic.

When ShareAI is a strong fit

• One API for a large set of models
• Flexibility across providers
• Routing and failover
• Visibility into model options and marketplace signals
• A cleaner path to production AI traffic
• A monetization layer for AI usage inside an app you already run

That last point matters for SaaS teams, open-source maintainers, self-hosted products, and agencies. If AI usage varies a lot across users or workspaces, ShareAI can help make the revenue model track the actual AI traffic instead of forcing one flat price on everyone.

FAQ

Do you need an AI gateway if you use one provider today?

Not always. But many teams add one before they scale because it reduces future switching costs and gives them better control over AI traffic.

Is ShareAI just an AI gateway?

No. ShareAI is better understood as an AI marketplace and API. The gateway-style value is part of the product, but the broader story includes marketplace visibility, Builder monetization, and a provider-powered network.

Can ShareAI help if we already have an application?

Yes. That is the Builder use case. You keep the app where it already lives, route AI inference traffic through ShareAI, and use ShareAI as the usage, billing, and payout layer.

What should teams compare when choosing an AI gateway?

Start with model access, routing options, failover, visibility into price and latency, developer experience, and how easily the product fits your existing stack.