The Multi-Model Challenge
Enterprises today have access to dozens of leading AI models, and domain-specific fine-tuned models on top of those. Each excels at different tasks and comes with different cost and latency profiles.
How Smart AI Selection Works
Intelligent Task Classification
When a skill or workflow step needs an AI model, smart AI selection:
- Analyzes the task requirements (complexity, domain, output format)
- Evaluates available models against these requirements
- Considers cost constraints and SLA requirements
- Routes to the optimal model automatically
Cost Optimization
Smart AI selection is designed to reduce AI inference cost without manual model selection:
- Simple tasks route to fast, efficient models
- Complex reasoning routes to the most capable models
- 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 available 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 We do not publish a generic savings number because the honest answer is "it depends on what your prompts look like."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
- 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