The Multi-Model Challenge
Enterprises today have access to dozens of AI models (GPT-4, Claude, Gemini, Llama, Mistral, and domain-specific fine-tuned models). Each excels at different tasks and comes with different cost and latency profiles.
How the Model Router Works
Intelligent Task Classification
When a skill or workflow step needs an AI model, the Model Router:
1Analyzes the task requirements (complexity, domain, output format)
2Evaluates available models against these requirements
3Considers cost constraints and SLA requirements
4Routes to the optimal model automatically
Cost Optimization
The Model Router is designed to reduce AI inference cost without manual model selection:
Simple tasks route to efficient models (Haiku, Gemini Flash)
Complex reasoning routes to capable models (Opus, GPT-4)
Batch processing uses discounted throughput tiers where supported by the provider
Token usage tracking with per-team budgets
Actual savings depend heavily on the workload mix and the price points of the models the router has access to in your tenant. We do not publish a generic savings number because the honest answer is "it depends on what your prompts look like."
Custom Model Support
Bring your own models:
Self-hosted open-source models (Llama, Mistral)
Fine-tuned models for domain-specific tasks
Private model endpoints with custom authentication
A/B testing between model configurations
Analytics Dashboard
Track model performance across your organization:
Per-model latency, cost, and quality metrics
Usage trends by team, skill, and workflow
Cost forecasting and budget alerts
Model comparison reports