ENTERPRISE
LLM Routing Platform
A task-aware AI routing infrastructure that dynamically selects the optimal language model based on cost, quality, complexity, and latency requirements.
MultiModel routing
CostOptimized selection
LatencyAware decisions
VerifyOutput checks
The challenge
Teams were using multiple language models with different quality, cost, and latency profiles. They needed a routing layer that could choose the right model per task, control spend, preserve response quality, and verify outputs before they reached users.
Our approach
- 1Designed a task-classification layer to estimate complexity and routing requirements.
- 2Built a multi-model routing engine that balances cost, latency, quality, and reliability.
- 3Added fallback and retry behavior for provider errors, timeouts, and degraded responses.
- 4Implemented output verification so high-risk responses could be checked before delivery.
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