Route across model vendors through one interface. Smart routing, automatic failover, and cost-aware policies so teams keep flexibility at the model layer without rewriting application logic.
A gateway node receiving agent requests and routing them to multiple LLM providers (GPT, Claude, Gemini) with failover arrows and latency indicators.
The model landscape changes fast. New providers launch, pricing shifts, and quality varies by task. Teams that hard-wire to a single LLM vendor inherit lock-in, fragile integrations, and limited leverage over cost and quality.
The LLM Gateway gives teams a single interface to access any supported model. Switching providers is a configuration change, not a migration.
Before and after: tangled direct integrations to multiple LLMs on the left, a clean single gateway interface on the right.
A routing decision tree showing different request types being directed to different LLM providers based on policy rules.
Not every request needs the same model. The LLM Gateway supports policy-based routing so teams can direct workloads based on cost, latency, performance, or data residency requirements.
Route premium requests to high-capability models and routine tasks to cost-efficient alternatives. Adjust routing as provider economics change without touching application code.
When a provider degrades or goes down, the gateway fails over to an alternative automatically. Agents keep running without manual intervention, and teams get notified so they can investigate without impacting live traffic.
Failover-ready architecture reduces dependence on any single upstream model or provider.
A provider going offline with traffic automatically rerouting to a healthy alternative, with a notification alert to the operations team.
A dashboard showing token usage, latency percentiles, error rates, and cost-per-call metrics broken down by LLM provider.
Every model call is traced, logged, and metered. Teams can monitor token consumption, response latency, error rates, and cost trends across providers from one dashboard.
This visibility helps teams make informed decisions about model selection, optimize spend, and detect quality drift before it impacts production.
Route across models with smart policies, automatic failover, and full visibility.