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Ask your spend · For a finance admin or a CEO

Plain-English questions, answered from the ledger

The problem today
A simple spend question means an export, a spreadsheet and a wait.
What it does
Answers in seconds. The model only writes a small query; code runs it on the ledger, so every figure is computed from the books.
What you see
The question, the query the model wrote, and the answer and chart computed from the ledger.

Internal benchmark on synthetic data · run run-20261022172600-test · spend questions in the test split

Fastest on this run: Mid-tier frontier. Most answers right: Mid-tier frontier. A wrong query gives a wrong total, but never a figure the ledger does not hold.

Show figures for each model
  • Dvar small model

    Answer right to the cent
    27 of 30
    Median time to the query
    1.57 s
    Model cost per question
    $0.00020
  • Low-cost frontier

    Answer right to the cent
    27 of 30
    Median time to the query
    714 ms
    Model cost per question
    $0.00011
  • Mid-tier frontier

    Answer right to the cent
    28 of 30
    Median time to the query
    533 ms
    Model cost per question
    $0.0028

Internal benchmark on synthetic data · run run-20261022172600-test · 2026-10-22 · 3 models, same instruction

Ask your spend

Ask about spend from April to October in plain words. Pick a question to start.

Behind the answer

Model
dvar:glm-5.3-flash
Time
—
Cost per question
—
Scorer
Press the button above

The scorer runs the model's query and the answer key's query over the same ledger and compares the results to the cent. A query that does not fit the shape is refused and nothing is shown.

Run run-20261022172600-test, 2026-10-22. Same instruction for every model, temperature 0. Cost is from tokens and list prices.

Why this is safe to put in front of a finance admin

  • The model writes a small JSON query, never a figure. Code checks its shape and runs it.
  • A query with an unknown field, a bad period or anything like SQL is refused before it runs.
  • The step is small (one short query per question), so it can be measured per model for accuracy, time and cost: see the table at the top of this page.