Definition · AI in finance
LLM router
LLM router is a layer that directs each query to the most suitable or cost-effective model. For LLM router, the useful boundary is the data it uses, the tools it can call, the approvals it needs, the review standard, and the finance decision it may influence before the output is trusted or automated.
Also known as model router, AI model routing
Why it matters
Understanding LLM router matters because AI-assisted finance work can sound confident even when data, assumptions, or compute paths are wrong. A useful definition keeps the output grounded, reviewable, and accountable. Because Pluvo is model-agnostic, it can route work across models for cost and capability while keeping your context and computed numbers in Pluvo.
In practice
Governance example
Teams use LLM router when they evaluate whether an AI-assisted analysis can be trusted. The useful test is whether the output is tied to approved data, repeatable logic, human review, and an audit trail.
Pluvo example
Because Pluvo is model-agnostic, it can route work across models for cost and capability while keeping your context and computed numbers in Pluvo.
In practice, teams should define LLM router with a clear source, owner, time period, and decision before they use it in reporting, planning, or operating reviews.
Understanding LLM router matters because AI-assisted finance work can sound confident even when data, assumptions, or compute paths are wrong. A useful definition keeps the output grounded, reviewable, and accountable. Because Pluvo is model-agnostic, it can route work across models for cost and capability while keeping your context and computed numbers in Pluvo.
A strong workflow for LLM router separates the definition from the action: first agree what the term means, then decide how it is measured, when it changes, and who is accountable for the next step.
Because Pluvo is model-agnostic, it can route work across models for cost and capability while keeping your context and computed numbers in Pluvo.
FAQ
What is an LLM router?
LLM router is a layer that directs each query to the most suitable or cost-effective model. For LLM router, the useful boundary is the data it uses, the tools it can call, the approvals it needs, the review standard, and the finance decision it may influence before the output is trusted or automated.
How does model routing reduce AI cost?
Reduce risk around LLM router by tying the workflow to approved data, explicit logic, review ownership, and an audit trail. The control should make the output explainable before it reaches reporting or decision-making.