The right model.
For every workload.
Manage local, foundation, and open-weight models together. Route by cost, meaning, latency, and policy while keeping provider failures from interrupting work.
- Understand the workloadText, audio, video, files, and coding.
- Apply routing policyCost, semantics, latency, and approved models.
- Keep requests movingLoad balance, handle failures, and switch models.
Model choice without operational sprawl.
Match model choice to the work.
Load balancing across model types
Distribute requests across local, foundation, and open-weight models. Keep sensitive workloads on approved infrastructure, especially in regulated industries.
Least-cost routing
Route work to the lowest-cost eligible model within your quality and policy requirements.
Semantic routing
Use the meaning and intent of a request to select a model suited to the task.
Latency-based routing
Choose eligible models based on latency so response time can guide routing alongside cost and capability.
Different workloads, different models
Manage text, audio, video, file uploads, and coding workloads with models that support the capabilities each task needs.
Model interworking
Coordinate models and providers within the same AI environment so different models can serve different parts of a workflow.
Build reliability into model access.
Automatic provider error handling
Handle rate limits and provider 5xx errors automatically, with retry and failover to eligible alternatives.
Fault tolerance
Maintain continuity when a provider or model becomes unavailable. Route around failures using the alternatives permitted by your policies.
Riskless model switching
Evaluate alternatives before changing models and keep approved fallback options available. Switch with confidence while keeping application access consistent.
Know when to stay. Know when to switch.
Automated monitoring, studies, and evaluation
Monitor model behavior and run model studies and evaluations to compare quality, cost, and latency on relevant workloads.
Explore Model Manager →Centralized key management
Manage provider keys centrally for your entire AI infrastructure. Control access through Cortega rather than distributing provider credentials across agents and applications.
Explore AI Border Gateway →MAKE YOUR NEXT MOVE
Put governance
into practice.
Explore how Cortega fits your AI environment.