What is an AI gateway?
An AI gateway is a unified access layer that sits between your applications and large language models — one endpoint and one set of credentials to reach many models through official channels, while routing, authentication, quota governance, observability, and data controls are handled in between.
As a team adopts several models at once, wiring each provider directly means juggling many endpoints, many keys, and inconsistent billing and governance. An AI gateway consolidates that into one place: a stable, unified interface on the inside, and controlled, observable, accountable calls on the outside.
Why teams use an AI gateway
Calling one or more models directly is quick to start, but at scale four problems show up — and an AI gateway exists to solve them:
Many models, many APIs
Different endpoints, keys, and SDKs across providers are costly to integrate and maintain.
Governance & cost
Without a unified view of quotas, keys, and spend, you can't see who used what, where.
Stability & continuity
Direct integrations are exposed to throttling, fluctuation, and outages; mission-critical work needs a dependable call layer.
Data & compliance
Calls carry sensitive data, which needs clear boundaries and an accountable party behind them.
What an AI gateway does
An AI gateway typically handles the following underneath, so your application faces just one stable interface:
Unified endpoint & routing
One address reaches many models, routing each call to the right model and version.
Auth & key management
Issue and revoke keys and permissions by team or project, centrally.
Quota & token governance
Allocate quotas, block overages, surface usage — keep cost under control.
Observability & billing
Logs, usage, and cost on one sheet — clear for reimbursement and audit.
Caching & performance
Cache where it fits, cutting latency and cost on repeat calls.
Reliability & recovery
Monitoring, alerts, and fast recovery so small issues don't snowball into downtime.
Data controls
Clear data boundaries: never captured, sold, or used for training.
Drop-in compatibility
Compatible with OpenAI and other major APIs; your existing SDK mostly unchanged.
Gateway vs direct vs cheap relay
Direct integration is simplest — your app talks to each model itself, fine for one or two models at small scale; once models multiply and you need governance and stability, you're left building that layer yourself. An AI gateway provides it: unified endpoint, governance, stability, and data controls.
How to choose an AI gateway
If AI runs in mission-critical work, check a candidate against these:
- Official channels, not reverse-engineered — straight through the official API, no model swaps.
- Full capability, not degraded — what you call is the real model, not a stand-in.
- Independent nodes & stability — no shared accounts, with monitoring and fast recovery.
- Clear data boundaries — never captured, sold, or trained on, written into the contract.
- Enterprise governance & transparent billing — quotas, keys, usage, reconciliation all in place.
- An accountable, incorporated entity — someone to reach when it matters.
- Delivery capability — not just connectivity, but help making AI actually work.
Solunar Gateway
Solunar Gateway is an AI gateway built to exactly these criteria: operated by Solunar AI Inc., an incorporated company in British Columbia, Canada; reaching mainstream models — flagship to open-source — through official channels; running on independent nodes; with data that stays yours, and end-to-end delivery from integration to rollout. Access is invite-only.