AI Assistant
How does Finance AI track AI usage costs?
Understand the admin Agent Costs dashboard, agent tags, per-user totals, and cache-aware cost estimates.
Quick answer
Finance AI records each user-triggered AI call with a required user ID, an enum agent tag, token usage, cached input tokens, Evlog metadata, and Finance AI's own cache-aware cost estimate.
Steps
- 1Open the Finance AI admin dashboard.
- 2Choose the Agent Costs tab.
- 3Select a range such as 1d, 7d, 30d, or 90d.
- 4Review tracked cost, average cost per user, users with usage, Evlog estimate, cache delta, and token totals.
- 5Use the By Tag, By Agent, By User, and By Model tables to isolate cost drivers.
- 6Select a user in the By User table to see that user's cost breakdown by agent and enum tag.
- 7Open Recent Calls to inspect the latest agent, tag, model, user, tracked cost, and Evlog estimate.
What gets recorded
Usage rows are tied to a user ID and a typed agent tag, such as Web Chat, Mobile Onboarding, Nightly Sync, Insights, Memory, Support, or Context Compaction. This lets the admin dashboard break cost down by both product surface and individual user.
Average cost per user is calculated from Finance AI's tracked cost divided by the number of users with usage in the selected range. The user breakdown lets admins click into one user and compare which agents and tags drove their cost.
Finance AI stores model token usage, cached input tokens, uncached input tokens, output tokens, reasoning tokens, local cost totals, Evlog AI metadata, and Evlog's estimated cost when it is available.
Why tracked cost can differ from Evlog
Evlog estimates model cost from input and output tokens. Finance AI also stores its own cost estimate because cached input tokens can be billed differently from ordinary input tokens.
The Cache delta metric compares Evlog's estimate with Finance AI's tracked cache-aware cost for the selected range. A larger delta usually means the model reused cached input.